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Multi-Sample Preference Optimization for Generative Model Alignment | 20548 | https://iclr.pangram.com/submissions?submission_number=20548 | Fully human-written | Soundness: 3: good
Presentation: 4: excellent
Contribution: 2: fair
Rating: 2: reject
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. | RLHF and DPO are popular post-training methodologies for LLM alignment. The standard method uses preference pairs consisting of single samples to align LLMs. This increases the probability of generating preferred samples when the reward is computed at a per-sample level. However, in several cases like increasing the di... | UIHe7r47ou | https://openreview.net/pdf?id=UIHe7r47ou | [
"Generative Models",
"LLM",
"Diffusion",
"RLHF",
"Preference Optimization"
] | foundation or frontier models, including LLMs | true | false | 3 | 4 | 2 | 2 | 4 | 4 | Negative |
Multi-Sample Preference Optimization for Generative Model Alignment | 20548 | https://iclr.pangram.com/submissions?submission_number=20548 | Fully human-written | Soundness: 3: good
Presentation: 4: excellent
Contribution: 3: good
Rating: 6: marginally above the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamilia... | This paper extends the direct preference alignment frameworks DPO and IPO to deal with preferences over groups of items over binary preference over pairs of items. The authors provide intuitive modifications to the DPO/IPO objective to incorporate group-wise comparisons, derive mini-batch estimators for these objective... | UIHe7r47ou | https://openreview.net/pdf?id=UIHe7r47ou | [
"Generative Models",
"LLM",
"Diffusion",
"RLHF",
"Preference Optimization"
] | foundation or frontier models, including LLMs | true | false | 3 | 4 | 3 | 6 | 4 | 4 | Negative |
Multi-Sample Preference Optimization for Generative Model Alignment | 20548 | https://iclr.pangram.com/submissions?submission_number=20548 | Lightly AI-edited | Soundness: 3: good
Presentation: 4: excellent
Contribution: 3: good
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamilia... | This paper introduces **multi-sample extensions of preference optimization methods (mDPO and mIPO)** for alignment. Whereas standard approaches such as RLHF and DPO/IPO rely on **single-sample pairwise comparisons**, this work proposes to instead optimize over distributions of responses. This allows the methods to capt... | UIHe7r47ou | https://openreview.net/pdf?id=UIHe7r47ou | [
"Generative Models",
"LLM",
"Diffusion",
"RLHF",
"Preference Optimization"
] | foundation or frontier models, including LLMs | true | false | 3 | 4 | 3 | 4 | 4 | 4 | Negative |
Multi-Sample Preference Optimization for Generative Model Alignment | 20548 | https://iclr.pangram.com/submissions?submission_number=20548 | Fully human-written | Soundness: 3: good
Presentation: 3: good
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | The paper proposes multi-sample variants of direct preference optimization methods (called mDPO and mIPO) that replace single response comparisons with group-wise comparisons aimed at aligning distributional properties (e.g., diversity, bias). In particular, the authors lift DPO/IPO from singletons to sets by using the... | UIHe7r47ou | https://openreview.net/pdf?id=UIHe7r47ou | [
"Generative Models",
"LLM",
"Diffusion",
"RLHF",
"Preference Optimization"
] | foundation or frontier models, including LLMs | true | false | 3 | 3 | 2 | 4 | 4 | 4 | Negative |
SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functions | 24026 | https://iclr.pangram.com/submissions?submission_number=24026 | Fully AI-generated | Soundness: 4: excellent
Presentation: 3: good
Contribution: 3: good
Rating: 8: accept, good paper
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar with some pieces of r... | SafeFlowMatcher meaningfully advances SafeDiffuser’s core idea—using CBFs to guarantee safety in generative planning—by swapping the stochastic, per-step–constrained diffusion backbone for a deterministic flow-matching model with a prediction–correction integrator and vanishing time-scaled CBF correction. This shift st... | refcXHU1Nh | https://openreview.net/pdf?id=refcXHU1Nh | [
"Flow matching",
"Safety guarantees",
"Planning and Control"
] | applications to robotics, autonomy, planning | true | false | 4 | 3 | 3 | 8 | 4 | 6 | Positive |
SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functions | 24026 | https://iclr.pangram.com/submissions?submission_number=24026 | Fully AI-generated | Soundness: 3: good
Presentation: 3: good
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 5: You are absolutely certain about your assessment. You are very familiar with the related work and checked the math/other details carefully. | This paper introduces SafeFlowMatcher, a novel planning framework that integrates Flow Matching (FM) with Control Barrier Functions (CBFs) to achieve both real-time efficiency and certified safety in robotic path planning. The core of SafeFlowMatcher is a two-phase Prediction-Correction (PC) integrator. The prediction ... | refcXHU1Nh | https://openreview.net/pdf?id=refcXHU1Nh | [
"Flow matching",
"Safety guarantees",
"Planning and Control"
] | applications to robotics, autonomy, planning | true | false | 3 | 3 | 2 | 4 | 5 | 6 | Positive |
SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functions | 24026 | https://iclr.pangram.com/submissions?submission_number=24026 | Fully human-written | Soundness: 3: good
Presentation: 3: good
Contribution: 3: good
Rating: 8: accept, good paper
Confidence: 3: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/other details were not carefu... | The paper introduces SafeFlowMatcher, a planning framework that integrates conditional flow matching with control barrier functions to generate trajectories that are efficient to sample and provably converge to a robust safe set. The method addresses a key limitation of flow-matching and diffusion planners, which produ... | refcXHU1Nh | https://openreview.net/pdf?id=refcXHU1Nh | [
"Flow matching",
"Safety guarantees",
"Planning and Control"
] | applications to robotics, autonomy, planning | true | false | 3 | 3 | 3 | 8 | 3 | 6 | Positive |
SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functions | 24026 | https://iclr.pangram.com/submissions?submission_number=24026 | Fully human-written | Soundness: 3: good
Presentation: 2: fair
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 3: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/other ... | The paper proposes SafeFlowMatcher, a planning framework that aims to combine Flow Matching (FM) generative models with the certified safety of Control Barrier Functions (CBFs). The core contribution is a two-phase "Prediction-Correction" (PC) integrator. First, a "Prediction" phase uses the learned FM model to generat... | refcXHU1Nh | https://openreview.net/pdf?id=refcXHU1Nh | [
"Flow matching",
"Safety guarantees",
"Planning and Control"
] | applications to robotics, autonomy, planning | true | false | 3 | 2 | 2 | 4 | 3 | 6 | Positive |
SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functions | 24026 | https://iclr.pangram.com/submissions?submission_number=24026 | Lightly AI-edited | Soundness: 3: good
Presentation: 3: good
Contribution: 3: good
Rating: 6: marginally above the acceptance threshold
Confidence: 2: You are willing to defend your assessment, but it is quite likely that you did not understand the central parts of the submission or that you are unfamiliar with some pieces of related work... | This paper presents SafeFlowMatcher, a novel framework for safe robotic path planning that
effectively couples generative Flow Matching (FM) with Control Barrier Functions (CBFs). The
authors identify a key problem with existing generative planners: they either lack formal safety
guarantees or, if certification-based, ... | refcXHU1Nh | https://openreview.net/pdf?id=refcXHU1Nh | [
"Flow matching",
"Safety guarantees",
"Planning and Control"
] | applications to robotics, autonomy, planning | true | false | 3 | 3 | 3 | 6 | 2 | 6 | Positive |
Principled Latent Diffusion for Graphs via Laplacian Autoencoders | 8966 | https://iclr.pangram.com/submissions?submission_number=8966 | Fully human-written | Soundness: 2: fair
Presentation: 3: good
Contribution: 3: good
Rating: 4: marginally below the acceptance threshold
Confidence: 2: You are willing to defend your assessment, but it is quite likely that you did not understand the central parts of the submission or that you are unfamiliar with some pieces of related work... | Graph generation suffers from quadratic complexity in the number of nodes stemming from the adjacency matrix, which, however, contains mostly zeros for most datasets. This hinders the generation of large graphs. The paper proposes a permutation-equivariant autoencoder that maps each node into a fixed-size latent space,... | hwGVfmRxuR | https://openreview.net/pdf?id=hwGVfmRxuR | [
"Graph generation",
"Latent diffusion"
] | generative models | true | false | 2 | 3 | 3 | 4 | 2 | 4.5 | Borderline |
Principled Latent Diffusion for Graphs via Laplacian Autoencoders | 8966 | https://iclr.pangram.com/submissions?submission_number=8966 | Fully human-written | Soundness: 3: good
Presentation: 4: excellent
Contribution: 4: excellent
Rating: 6: marginally above the acceptance threshold
Confidence: 5: You are absolutely certain about your assessment. You are very familiar with the related work and checked the math/other details carefully. | This article proposes a nearly lossless latent graph diffusion method in view of the high complexity limitations of the existing graph diffusion models due to the discrete paradigm. Specifically, considering the strict requirements of graph data for reconstructing encoder-decoder, the authors proposed a Laplacian autoe... | hwGVfmRxuR | https://openreview.net/pdf?id=hwGVfmRxuR | [
"Graph generation",
"Latent diffusion"
] | generative models | true | false | 3 | 4 | 4 | 6 | 5 | 4.5 | Borderline |
Principled Latent Diffusion for Graphs via Laplacian Autoencoders | 8966 | https://iclr.pangram.com/submissions?submission_number=8966 | Fully human-written | Soundness: 1: poor
Presentation: 2: fair
Contribution: 3: good
Rating: 4: marginally below the acceptance threshold
Confidence: 3: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/other ... | ML graph generation models suffer from poor scalability due to quadratic cost of graph representation and hardness to compress such graphs into revertible latent representation. LG-VAE poses itself as a variational autoencoder that uses the graph laplacian spectrum to bring provable reversibility and enable fast graph ... | hwGVfmRxuR | https://openreview.net/pdf?id=hwGVfmRxuR | [
"Graph generation",
"Latent diffusion"
] | generative models | true | false | 1 | 2 | 3 | 4 | 3 | 4.5 | Borderline |
Principled Latent Diffusion for Graphs via Laplacian Autoencoders | 8966 | https://iclr.pangram.com/submissions?submission_number=8966 | Lightly AI-edited | Soundness: 3: good
Presentation: 2: fair
Contribution: 3: good
Rating: 4: marginally below the acceptance threshold
Confidence: 3: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/other ... | The paper proposes a latent diffusion framework for graph generation that uses an autoencoder with Laplacian based adjacency identifying positional encodings. The decoder applies bilinear attention style scoring and a row wise DeepSet, and the approach extends to DAGs via a magnetic Laplacian. The authors claim that af... | hwGVfmRxuR | https://openreview.net/pdf?id=hwGVfmRxuR | [
"Graph generation",
"Latent diffusion"
] | generative models | true | false | 3 | 2 | 3 | 4 | 3 | 4.5 | Borderline |
CGTFra: General Graph Transformer Framework for Consistent Inter-series Dependency Modeling in Multivariate Time Series | 7185 | https://iclr.pangram.com/submissions?submission_number=7185 | Moderately AI-edited | Soundness: 3: good
Presentation: 2: fair
Contribution: 3: good
Rating: 4: marginally below the acceptance threshold
Confidence: 5: You are absolutely certain about your assessment. You are very familiar with the related work and checked the math/other details carefully. | The author defines the problem of inter-variate dependencies (IVD), referring to the loss of dependency information among variables in deep self-attention layers. To address this issue, the authors propose CGTFra, a framework designed to promote consistent modeling of inter-variate dependencies.
S1. The author makes a ... | li0Wg2LryZ | https://openreview.net/pdf?id=li0Wg2LryZ | [
"Graph transformer",
"Multivariate time series forecasting",
"Intra-series dependency modeling",
"Inter-series dependency modeling"
] | learning on time series and dynamical systems | true | false | 3 | 2 | 3 | 4 | 5 | 4 | Negative |
CGTFra: General Graph Transformer Framework for Consistent Inter-series Dependency Modeling in Multivariate Time Series | 7185 | https://iclr.pangram.com/submissions?submission_number=7185 | Fully human-written | Soundness: 3: good
Presentation: 2: fair
Contribution: 3: good
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | This paper proposes a Graph Transformer framework CGTFra with adaptive frequency masking and resampling method and dynamic graph learning framework, which can diminish the importance of timestamps and promote consistent inter-variate dependencies (IVD) modeling. Experiments demonstrate the effectiveness of CGTFra.
1.In... | li0Wg2LryZ | https://openreview.net/pdf?id=li0Wg2LryZ | [
"Graph transformer",
"Multivariate time series forecasting",
"Intra-series dependency modeling",
"Inter-series dependency modeling"
] | learning on time series and dynamical systems | true | false | 3 | 2 | 3 | 4 | 4 | 4 | Negative |
CGTFra: General Graph Transformer Framework for Consistent Inter-series Dependency Modeling in Multivariate Time Series | 7185 | https://iclr.pangram.com/submissions?submission_number=7185 | Lightly AI-edited | Soundness: 3: good
Presentation: 3: good
Contribution: 3: good
Rating: 6: marginally above the acceptance threshold
Confidence: 5: You are absolutely certain about your assessment. You are very familiar with the related work and checked the math/other details carefully. | This paper addresses two limitations of Transformers in multivariate time series forecasting by proposing the CGTFra framework: (1) it introduces frequency-domain masking and resampling methods to replace positional encoding, thereby reducing dependence on timestamp information; (2) it incorporates a dynamic graph lear... | li0Wg2LryZ | https://openreview.net/pdf?id=li0Wg2LryZ | [
"Graph transformer",
"Multivariate time series forecasting",
"Intra-series dependency modeling",
"Inter-series dependency modeling"
] | learning on time series and dynamical systems | true | false | 3 | 3 | 3 | 6 | 5 | 4 | Negative |
CGTFra: General Graph Transformer Framework for Consistent Inter-series Dependency Modeling in Multivariate Time Series | 7185 | https://iclr.pangram.com/submissions?submission_number=7185 | Moderately AI-edited | Soundness: 2: fair
Presentation: 2: fair
Contribution: 2: fair
Rating: 2: reject
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. | This paper proposes CGTFra, a General Graph Transformer Framework for multivariate time series forecasting. The core idea is to model both the temporal dependencies and inter-variable correlations using a unified graph-transformer paradigm. Experiments on several real-world datasets demonstrate that CGTFra achieves con... | li0Wg2LryZ | https://openreview.net/pdf?id=li0Wg2LryZ | [
"Graph transformer",
"Multivariate time series forecasting",
"Intra-series dependency modeling",
"Inter-series dependency modeling"
] | learning on time series and dynamical systems | true | false | 2 | 2 | 2 | 2 | 4 | 4 | Negative |
MorphGen: Controllable and Morphologically Plausible Generative Cell-Imaging | 17062 | https://iclr.pangram.com/submissions?submission_number=17062 | Fully AI-generated | Soundness: 3: good
Presentation: 3: good
Contribution: 3: good
Rating: 6: marginally above the acceptance threshold
Confidence: 5: You are absolutely certain about your assessment. You are very familiar with the related work and checked the math/other details carefully. | This paper presents MorphGen, a diffusion-based generative model for Cell Painting microscopy images that achieves controllable generation across multiple cell types and perturbations. The key innovation is an alignment loss that guides MorphGen’s internal representations to match those of OpenPhenom (Kraus et al., 202... | t6Q9B6jUQt | https://openreview.net/pdf?id=t6Q9B6jUQt | [
"Generative Modelling",
"Latent Diffusion Model",
"Cell Painting",
"Morphology",
"Phenotypical Response"
] | generative models | true | false | 3 | 3 | 3 | 6 | 5 | 4 | Negative |
MorphGen: Controllable and Morphologically Plausible Generative Cell-Imaging | 17062 | https://iclr.pangram.com/submissions?submission_number=17062 | Fully human-written | Soundness: 2: fair
Presentation: 3: good
Contribution: 2: fair
Rating: 2: reject
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. | In this work, the authors propose Morphegen, a generative model to predict the morphological cellular responses to perturbations. They introduce strategies to make this framework compatible with the multi-channel nature of HCS imaging. The authors performed a series of experiments to validate the performance of the met... | t6Q9B6jUQt | https://openreview.net/pdf?id=t6Q9B6jUQt | [
"Generative Modelling",
"Latent Diffusion Model",
"Cell Painting",
"Morphology",
"Phenotypical Response"
] | generative models | true | false | 2 | 3 | 2 | 2 | 4 | 4 | Negative |
MorphGen: Controllable and Morphologically Plausible Generative Cell-Imaging | 17062 | https://iclr.pangram.com/submissions?submission_number=17062 | Fully human-written | Soundness: 3: good
Presentation: 2: fair
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | This paper develops MorphGen, a diffusion model for generating cell painting images conditioned on a description of a perturbation and cell type. There are previous approaches for this task, but two key advantages of MorphGen are the ability to natively model all 6 channels of cell painting data and the ability to inco... | t6Q9B6jUQt | https://openreview.net/pdf?id=t6Q9B6jUQt | [
"Generative Modelling",
"Latent Diffusion Model",
"Cell Painting",
"Morphology",
"Phenotypical Response"
] | generative models | true | false | 3 | 2 | 2 | 4 | 4 | 4 | Negative |
OpenAVS: Training-Free Open-Set Audio Visual Segmentation with Foundational Models | 6561 | https://iclr.pangram.com/submissions?submission_number=6561 | Lightly AI-edited | Soundness: 3: good
Presentation: 3: good
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | The authors propose OpenAVS, a novel training-free language-based approach that, for the first time, effectively aligns audio and visual via a text proxy for open-vocabulary AVS. But there is still work to do.
1. The method seems feasible.
2. The writing is clear and easy to read.
3. Enough visualization is provided.
1... | sgvL0zuDeZ | https://openreview.net/pdf?id=sgvL0zuDeZ | [
"Open-Vocabulary Audio-Visual Segmentation",
"Multimedia Foundation Models",
"Large Language Models"
] | applications to computer vision, audio, language, and other modalities | true | false | 3 | 3 | 2 | 4 | 4 | 3.5 | Negative |
OpenAVS: Training-Free Open-Set Audio Visual Segmentation with Foundational Models | 6561 | https://iclr.pangram.com/submissions?submission_number=6561 | Lightly AI-edited | Soundness: 3: good
Presentation: 3: good
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 5: You are absolutely certain about your assessment. You are very familiar with the related work and checked the math/other details carefully. | This paper introduce a novel training-free language-based approach for open-set audio visual segmentation.
The language-based method achieves more robust audio-visual alignment than existing methods.
This is a flexible and cost-efficient framework, and achieves state-of-the-art performance on four benchmark and traini... | sgvL0zuDeZ | https://openreview.net/pdf?id=sgvL0zuDeZ | [
"Open-Vocabulary Audio-Visual Segmentation",
"Multimedia Foundation Models",
"Large Language Models"
] | applications to computer vision, audio, language, and other modalities | true | false | 3 | 3 | 2 | 4 | 5 | 3.5 | Negative |
OpenAVS: Training-Free Open-Set Audio Visual Segmentation with Foundational Models | 6561 | https://iclr.pangram.com/submissions?submission_number=6561 | Fully human-written | Soundness: 2: fair
Presentation: 3: good
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 5: You are absolutely certain about your assessment. You are very familiar with the related work and checked the math/other details carefully. | This paper focuses on audio-visual segmentation, i.e., separating sounding objects from videos by predicting pixel-level masks of audio signals. Instead of direct audio-text alignment, this paper use one training-free idea, namely OpenAVS, to aligns audio and visual via text proxy. And the pipeline is divided into audi... | sgvL0zuDeZ | https://openreview.net/pdf?id=sgvL0zuDeZ | [
"Open-Vocabulary Audio-Visual Segmentation",
"Multimedia Foundation Models",
"Large Language Models"
] | applications to computer vision, audio, language, and other modalities | true | false | 2 | 3 | 2 | 4 | 5 | 3.5 | Negative |
OpenAVS: Training-Free Open-Set Audio Visual Segmentation with Foundational Models | 6561 | https://iclr.pangram.com/submissions?submission_number=6561 | Lightly AI-edited | Soundness: 2: fair
Presentation: 3: good
Contribution: 1: poor
Rating: 2: reject
Confidence: 5: You are absolutely certain about your assessment. You are very familiar with the related work and checked the math/other details carefully. | The manuscript proposes a training-free, open-vocabulary audio-visual segmentation (AVS) framework, OpenAVS, which uses language as a mediator to alleviate cross-modal misalignment in multi-source and temporally drifting scenarios. The method first converts audio and visual frames into semantic text via audio language ... | sgvL0zuDeZ | https://openreview.net/pdf?id=sgvL0zuDeZ | [
"Open-Vocabulary Audio-Visual Segmentation",
"Multimedia Foundation Models",
"Large Language Models"
] | applications to computer vision, audio, language, and other modalities | true | false | 2 | 3 | 1 | 2 | 5 | 3.5 | Negative |
Teach to Reason Safely: Policy-Guided Safety Tuning for MLRMs | 1280 | https://iclr.pangram.com/submissions?submission_number=1280 | Lightly AI-edited | Soundness: 3: good
Presentation: 3: good
Contribution: 2: fair
Rating: 6: marginally above the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | The authors present evidence that multi-modal reasoning models significantly outperform multi-modal base models on complex tasks; however, this improvement also leads to an increase in the generation of harmful content. Through experimental analysis, they identify two primary causes: 1) visual attention drift and 2) un... | cgy4i74Dq7 | https://openreview.net/pdf?id=cgy4i74Dq7 | [
"MLRM",
"safety",
"alignment",
"safety-helpfulness trade-off"
] | alignment, fairness, safety, privacy, and societal considerations | true | false | 3 | 3 | 2 | 6 | 4 | 4.5 | Borderline |
Teach to Reason Safely: Policy-Guided Safety Tuning for MLRMs | 1280 | https://iclr.pangram.com/submissions?submission_number=1280 | Lightly AI-edited | Soundness: 1: poor
Presentation: 2: fair
Contribution: 2: fair
Rating: 2: reject
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. | The paper studies a safety–reasoning trade-off in Multimodal Large Reasoning Models (MLRMs): reasoning-tuned models produce more harmful outputs than their base counterparts. It analyzes two mechanisms—(i) visual attention drift that weakens visual grounding and (ii) unsafe reasoning patterns such as flawed reasoning i... | cgy4i74Dq7 | https://openreview.net/pdf?id=cgy4i74Dq7 | [
"MLRM",
"safety",
"alignment",
"safety-helpfulness trade-off"
] | alignment, fairness, safety, privacy, and societal considerations | true | false | 1 | 2 | 2 | 2 | 4 | 4.5 | Borderline |
Teach to Reason Safely: Policy-Guided Safety Tuning for MLRMs | 1280 | https://iclr.pangram.com/submissions?submission_number=1280 | Fully human-written | Soundness: 3: good
Presentation: 3: good
Contribution: 2: fair
Rating: 6: marginally above the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | The paper
- Illustrates that reasoning VLMs generate harmful outputs at a higher rate than their non-reasoning counterparts.
- Introduces a multi-step data generation pipeline that generates policy-specific reasoning traces on the basis of text-image samples from the Beavertails-V dataset.
- The data generation pipelin... | cgy4i74Dq7 | https://openreview.net/pdf?id=cgy4i74Dq7 | [
"MLRM",
"safety",
"alignment",
"safety-helpfulness trade-off"
] | alignment, fairness, safety, privacy, and societal considerations | true | false | 3 | 3 | 2 | 6 | 4 | 4.5 | Borderline |
Teach to Reason Safely: Policy-Guided Safety Tuning for MLRMs | 1280 | https://iclr.pangram.com/submissions?submission_number=1280 | Moderately AI-edited | Soundness: 2: fair
Presentation: 3: good
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | This paper investigates the safety-reasoning trade-off in Multimodal Large Reasoning Models (MLRMs), highlighting that improved reasoning often coincides with increased harmful output rates. The authors identify two key mechanisms behind safety degradation—visual attention drift and unsafe reasoning patterns. To addres... | cgy4i74Dq7 | https://openreview.net/pdf?id=cgy4i74Dq7 | [
"MLRM",
"safety",
"alignment",
"safety-helpfulness trade-off"
] | alignment, fairness, safety, privacy, and societal considerations | true | false | 2 | 3 | 2 | 4 | 4 | 4.5 | Borderline |
AQuA: Toward Strategic Response Generation for Ambiguous Visual Questions | 10855 | https://iclr.pangram.com/submissions?submission_number=10855 | Fully human-written | Soundness: 3: good
Presentation: 3: good
Contribution: 3: good
Rating: 6: marginally above the acceptance threshold
Confidence: 3: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/other ... | The paper introduces AQUA, a dataset trying to solve the ambiguity issues in VQA. There are four fine-grained levels. This work fine-tunes VLMs with SFT followed by GRPO using an LLM-as-a-judge reward. Fine-tuning small models substantially improves the accuracy across ambiguity levels, outperforming larger open- and c... | 7b1MpD6IF8 | https://openreview.net/pdf?id=7b1MpD6IF8 | [
"Visual Question Answering",
"Vision–Language Models"
] | applications to computer vision, audio, language, and other modalities | true | false | 3 | 3 | 3 | 6 | 3 | 5.5 | Borderline |
AQuA: Toward Strategic Response Generation for Ambiguous Visual Questions | 10855 | https://iclr.pangram.com/submissions?submission_number=10855 | Moderately AI-edited | Soundness: 3: good
Presentation: 3: good
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 3: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/other ... | This paper tackles an interesting problem: teaching VLMs to handle ambiguous questions through strategic responses across four ambiguity levels. The motivation is solid and the experiments are thorough, but I have concerns about the heavy reliance on GPT-5 throughout the entire pipeline, the small dataset size, and som... | 7b1MpD6IF8 | https://openreview.net/pdf?id=7b1MpD6IF8 | [
"Visual Question Answering",
"Vision–Language Models"
] | applications to computer vision, audio, language, and other modalities | true | false | 3 | 3 | 2 | 4 | 3 | 5.5 | Borderline |
AQuA: Toward Strategic Response Generation for Ambiguous Visual Questions | 10855 | https://iclr.pangram.com/submissions?submission_number=10855 | Fully human-written | Soundness: 2: fair
Presentation: 4: excellent
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamilia... | The paper introduces a new fine-grained dataset AQuA with ambiguous questions that requires vision-language models to recognize when they cannot answer a question. Most models answer ambiguous questions confidently instead of abstaining or seeking clarifications. The paper defines a 4-level categorization of question a... | 7b1MpD6IF8 | https://openreview.net/pdf?id=7b1MpD6IF8 | [
"Visual Question Answering",
"Vision–Language Models"
] | applications to computer vision, audio, language, and other modalities | true | false | 2 | 4 | 2 | 4 | 4 | 5.5 | Borderline |
AQuA: Toward Strategic Response Generation for Ambiguous Visual Questions | 10855 | https://iclr.pangram.com/submissions?submission_number=10855 | Fully human-written | Soundness: 3: good
Presentation: 3: good
Contribution: 3: good
Rating: 8: accept, good paper
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar with some pieces of relate... | The paper proposes a new benchmark dataset for training and evaluating Vision–Language Models (VLMs), specifically on how to handle different types and degrees of ambiguity in visual questions. The differentiating idea is to extend the binary abstention decision to a four-level taxonomy of ambiguity. Also, the dataset ... | 7b1MpD6IF8 | https://openreview.net/pdf?id=7b1MpD6IF8 | [
"Visual Question Answering",
"Vision–Language Models"
] | applications to computer vision, audio, language, and other modalities | true | false | 3 | 3 | 3 | 8 | 4 | 5.5 | Borderline |
LaVCa: LLM-assisted Visual Cortex Captioning | 19639 | https://iclr.pangram.com/submissions?submission_number=19639 | Lightly AI-edited | Soundness: 3: good
Presentation: 4: excellent
Contribution: 3: good
Rating: 6: marginally above the acceptance threshold
Confidence: 3: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/o... | This paper introduces LaVCa, a novel framework that leverages large language models (LLMs) to generate natural-language captions describing the selectivity of individual fMRI voxels in the human brain cortex. Although the proposed framework appears complex, the only trainable component is a standard voxel-wise ridge re... | QlsjfYADcg | https://openreview.net/pdf?id=QlsjfYADcg | [
"Neuroscience",
"Computer vision",
"Visual systems",
"Captioning",
"Large language model",
"Semantics",
"Neuroimaging",
"Functional magnetic resonance imaging"
] | applications to neuroscience & cognitive science | true | false | 3 | 4 | 3 | 6 | 3 | 5.5 | Borderline |
LaVCa: LLM-assisted Visual Cortex Captioning | 19639 | https://iclr.pangram.com/submissions?submission_number=19639 | Fully human-written | Soundness: 3: good
Presentation: 3: good
Contribution: 2: fair
Rating: 6: marginally above the acceptance threshold
Confidence: 5: You are absolutely certain about your assessment. You are very familiar with the related work and checked the math/other details carefully. | This paper investigates the selectivity of voxels in the human visual cortex by generating a descriptive caption for each voxel.
To briefly summarize what the authors do:
1. First they build voxel-wise encoding models using embeddings from CLIP
2. They identify the "optimal images" that most strongly activate a specif... | QlsjfYADcg | https://openreview.net/pdf?id=QlsjfYADcg | [
"Neuroscience",
"Computer vision",
"Visual systems",
"Captioning",
"Large language model",
"Semantics",
"Neuroimaging",
"Functional magnetic resonance imaging"
] | applications to neuroscience & cognitive science | true | false | 3 | 3 | 2 | 6 | 5 | 5.5 | Borderline |
LaVCa: LLM-assisted Visual Cortex Captioning | 19639 | https://iclr.pangram.com/submissions?submission_number=19639 | Fully AI-generated | Soundness: 4: excellent
Presentation: 4: excellent
Contribution: 3: good
Rating: 6: marginally above the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfa... | LaVCa introduces a data-driven approach for describing the selectivity of individual human brain voxels in the visual cortex using captions generated by large language models (LLMs). The proposed method trains encoding models for fMRI activity in response to images, isolates the most selective images for each voxel, us... | QlsjfYADcg | https://openreview.net/pdf?id=QlsjfYADcg | [
"Neuroscience",
"Computer vision",
"Visual systems",
"Captioning",
"Large language model",
"Semantics",
"Neuroimaging",
"Functional magnetic resonance imaging"
] | applications to neuroscience & cognitive science | true | false | 4 | 4 | 3 | 6 | 4 | 5.5 | Borderline |
LaVCa: LLM-assisted Visual Cortex Captioning | 19639 | https://iclr.pangram.com/submissions?submission_number=19639 | Fully human-written | Soundness: 3: good
Presentation: 3: good
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | This paper proposes a novel LLM-based pipeline for fMRI interpretation at the voxel level. The authors leverage the natural scenes dataset, and use the learned encoding weights from a VLM on NSD to predict fMRI responses to a novel set of images. They select the image set that produces the highest predicted response fo... | QlsjfYADcg | https://openreview.net/pdf?id=QlsjfYADcg | [
"Neuroscience",
"Computer vision",
"Visual systems",
"Captioning",
"Large language model",
"Semantics",
"Neuroimaging",
"Functional magnetic resonance imaging"
] | applications to neuroscience & cognitive science | true | false | 3 | 3 | 2 | 4 | 4 | 5.5 | Borderline |
Salient Object Ranking via Cyclical Perception-Viewing Interaction Modeling | 12193 | https://iclr.pangram.com/submissions?submission_number=12193 | Fully human-written | Soundness: 2: fair
Presentation: 3: good
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | This paper proposed a method for saliency object ranking. A story prediction module predicts the caption of the image and a guided ranking module predicts the saliency rankings. The cyclical interaction module aligns and refines the caption and the ranking iteratively. The experimental results seemed to show the propos... | RDOlvzwSyF | https://openreview.net/pdf?id=RDOlvzwSyF | [
"Saliency Ranking",
"Human Attention Shift Modeling"
] | applications to computer vision, audio, language, and other modalities | true | false | 2 | 3 | 2 | 4 | 4 | 5.33 | Borderline |
Salient Object Ranking via Cyclical Perception-Viewing Interaction Modeling | 12193 | https://iclr.pangram.com/submissions?submission_number=12193 | Lightly AI-edited | Soundness: 3: good
Presentation: 3: good
Contribution: 3: good
Rating: 6: marginally above the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | The authors propose a Salient Object Ranking (SOR) approach that consists of two modules: the Guided Ranking (GR) module and the Story Prediction (SP) module, whose interaction enhances the overall performance of SOR.
The design of this model aligns well with the human cognitive system, such as predictive coding, and t... | RDOlvzwSyF | https://openreview.net/pdf?id=RDOlvzwSyF | [
"Saliency Ranking",
"Human Attention Shift Modeling"
] | applications to computer vision, audio, language, and other modalities | true | false | 3 | 3 | 3 | 6 | 4 | 5.33 | Borderline |
Salient Object Ranking via Cyclical Perception-Viewing Interaction Modeling | 12193 | https://iclr.pangram.com/submissions?submission_number=12193 | Fully human-written | Soundness: 3: good
Presentation: 2: fair
Contribution: 3: good
Rating: 6: marginally above the acceptance threshold
Confidence: 3: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/other ... | This paper proposes a novel framework that models the cyclical interaction between perception and viewing for the Salient Object Ranking (SOR) task. The method introduces two key components: a Story Prediction (SP) module that simulates the human perceptual process through image caption generation, and a Guided Ranking... | RDOlvzwSyF | https://openreview.net/pdf?id=RDOlvzwSyF | [
"Saliency Ranking",
"Human Attention Shift Modeling"
] | applications to computer vision, audio, language, and other modalities | true | false | 3 | 2 | 3 | 6 | 3 | 5.33 | Borderline |
RECTOR: Masked Region-Channel-Temporal Modeling for Cognitive Representation Learning | 24659 | https://iclr.pangram.com/submissions?submission_number=24659 | Fully AI-generated | Soundness: 3: good
Presentation: 3: good
Contribution: 3: good
Rating: 4: marginally below the acceptance threshold
Confidence: 5: You are absolutely certain about your assessment. You are very familiar with the related work and checked the math/other details carefully. | This paper introduces RECTOR, a self-supervised framework for EEG/sEEG data that integrates region, channel, and temporal representation learning through a novel hierarchical self-attention mechanism (RECTOR-SA). The model incorporates anatomical priors and functional attention to capture complex spatio-temporal intera... | wxDIEcPow9 | https://openreview.net/pdf?id=wxDIEcPow9 | [
"self-supervised learning",
"self-attention mechanism",
"masked modeling",
"contrastive learning",
"EEG",
"sEEG",
"affective and cognitive disorders"
] | applications to neuroscience & cognitive science | true | false | 3 | 3 | 3 | 4 | 5 | 3.5 | Negative |
RECTOR: Masked Region-Channel-Temporal Modeling for Cognitive Representation Learning | 24659 | https://iclr.pangram.com/submissions?submission_number=24659 | Heavily AI-edited | Soundness: 3: good
Presentation: 1: poor
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | This paper proposes RECTOR, a self-supervised framework for EEG and sEEG cognitive representation learning that explicitly models region–channel–temporal interactions. The key contributions include: (1) RECTOR-SA, a hierarchical sparse attention mechanism incorporating anatomical priors and dynamic gating; (2) RECTOR-M... | wxDIEcPow9 | https://openreview.net/pdf?id=wxDIEcPow9 | [
"self-supervised learning",
"self-attention mechanism",
"masked modeling",
"contrastive learning",
"EEG",
"sEEG",
"affective and cognitive disorders"
] | applications to neuroscience & cognitive science | true | false | 3 | 1 | 2 | 4 | 4 | 3.5 | Negative |
RECTOR: Masked Region-Channel-Temporal Modeling for Cognitive Representation Learning | 24659 | https://iclr.pangram.com/submissions?submission_number=24659 | Fully human-written | Soundness: 3: good
Presentation: 2: fair
Contribution: 3: good
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | This papers introduces a complete and exhaustive method for self-supervised deep learning framework for EEG and sEEG data, accounting the various aspects and dynamics of these brain activity modalities (region, channels, temporal). It introduces multiple modules, in particular RECTOR-SA and RECTOR-Mask, for feature ext... | wxDIEcPow9 | https://openreview.net/pdf?id=wxDIEcPow9 | [
"self-supervised learning",
"self-attention mechanism",
"masked modeling",
"contrastive learning",
"EEG",
"sEEG",
"affective and cognitive disorders"
] | applications to neuroscience & cognitive science | true | false | 3 | 2 | 3 | 4 | 4 | 3.5 | Negative |
RECTOR: Masked Region-Channel-Temporal Modeling for Cognitive Representation Learning | 24659 | https://iclr.pangram.com/submissions?submission_number=24659 | Fully AI-generated | Soundness: 2: fair
Presentation: 2: fair
Contribution: 2: fair
Rating: 2: reject
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. | The paper *RECTOR: Masked Region–Channel–Temporal Modeling for Cognitive Representation Learning* proposes RECTOR, a self-supervised learning framework for EEG and sEEG representation learning that jointly models region-, channel-, and temporal-level dependencies. Its core contributions include a novel **RECTOR-SA** hi... | wxDIEcPow9 | https://openreview.net/pdf?id=wxDIEcPow9 | [
"self-supervised learning",
"self-attention mechanism",
"masked modeling",
"contrastive learning",
"EEG",
"sEEG",
"affective and cognitive disorders"
] | applications to neuroscience & cognitive science | true | false | 2 | 2 | 2 | 2 | 4 | 3.5 | Negative |
Constructing a 3D Scene from a Single Image | 13109 | https://iclr.pangram.com/submissions?submission_number=13109 | Fully human-written | Soundness: 3: good
Presentation: 2: fair
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar wit... | This paper proposes an image-to-3D method by leveraging 3D generative model, trellis, as a backbone to generate 3D scenes. It starts with depth estimation to obtain the sparse structure of the scene, and then a structured latent is generated region-by-region using masked rectified flow, which is then fed into decoder... | TPJEZDn5zo | https://openreview.net/pdf?id=TPJEZDn5zo | [
"Image-to-3D Generation",
"3D Scene Generation"
] | applications to computer vision, audio, language, and other modalities | true | false | 3 | 2 | 2 | 4 | 4 | 5.5 | Borderline |
Constructing a 3D Scene from a Single Image | 13109 | https://iclr.pangram.com/submissions?submission_number=13109 | Fully human-written | Soundness: 4: excellent
Presentation: 3: good
Contribution: 3: good
Rating: 8: accept, good paper
Confidence: 4: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar with some pieces of r... | The paper presents a training-free method for creating 3D scenes from single images by fusing region-based generations. The key problem identified is in maintaining the structural consistency within partial generations during generation and completion. This is resolved by applying a sequence of techniques derived from ... | TPJEZDn5zo | https://openreview.net/pdf?id=TPJEZDn5zo | [
"Image-to-3D Generation",
"3D Scene Generation"
] | applications to computer vision, audio, language, and other modalities | true | false | 4 | 3 | 3 | 8 | 4 | 5.5 | Borderline |
Constructing a 3D Scene from a Single Image | 13109 | https://iclr.pangram.com/submissions?submission_number=13109 | Lightly AI-edited | Soundness: 3: good
Presentation: 2: fair
Contribution: 2: fair
Rating: 4: marginally below the acceptance threshold
Confidence: 3: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/other ... | The paper proposes SceneFuse-3D, a training-free, modular pipeline for turning a single top-down image into a coherent, editable 3D scene. The core contributions are: (1) region-based generation that splits a scene-level structured latent into overlapping patches; (2) a spatial prior built from monocular depth and land... | TPJEZDn5zo | https://openreview.net/pdf?id=TPJEZDn5zo | [
"Image-to-3D Generation",
"3D Scene Generation"
] | applications to computer vision, audio, language, and other modalities | true | false | 3 | 2 | 2 | 4 | 3 | 5.5 | Borderline |
Constructing a 3D Scene from a Single Image | 13109 | https://iclr.pangram.com/submissions?submission_number=13109 | Fully human-written | Soundness: 3: good
Presentation: 3: good
Contribution: 3: good
Rating: 6: marginally above the acceptance threshold
Confidence: 3: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/other ... | This paper tackles the problem of scene-level 3D generation from (bird-eye-view) images. The motivation and contribution is clear.
The proposed solution is intuitive and effective. Using point-cloud from monocular depth estimation as a guidance helps improve the scene-level consistency. Regional alignment and extrapol... | TPJEZDn5zo | https://openreview.net/pdf?id=TPJEZDn5zo | [
"Image-to-3D Generation",
"3D Scene Generation"
] | applications to computer vision, audio, language, and other modalities | true | false | 3 | 3 | 3 | 6 | 3 | 5.5 | Borderline |
LeGIT: LLM Guided Intervention Targeting for Online Causal Discovery | 24359 | https://iclr.pangram.com/submissions?submission_number=24359 | Fully human-written | Soundness: 1: poor
Presentation: 3: good
Contribution: 1: poor
Rating: 2: reject
Confidence: 3: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/other details were not carefully checked. | The work explores the usage of LLMs for experimental design. The authors propose a framework and prompts for acquiring information about root causes in the network from LLMs. This information guides further experimentation. The approach is compared to several baselines on four real-world inspired problems using the ENC... | cdxFCHQQnU | https://openreview.net/pdf?id=cdxFCHQQnU | [
"Large Language Model",
"Experimental Design",
"Causal Discovery"
] | foundation or frontier models, including LLMs | true | false | 1 | 3 | 1 | 2 | 3 | 3.5 | Negative |
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