yusuke1997/dblp-id-title huggingface dataset:
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module
From Promise to Practice: Realizing High-performance Decentralized Training
Subspace Regularizers for Few-Shot Class Incremental Learning
Towards Multiple Character Image Animation Through Enhancing Implicit Decoupling
Provably Safeguarding a Classifier from OOD and Adversarial Samples
DeepSphere: a graph-based spherical CNN
Multi-Domain Adversarial Learning
Identifying Representations for Intervention Extrapolation
Identifying Physical Law of Hamiltonian Systems via Meta-Learning
Deep Information Propagation
VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections
TVNet: A Novel Time Series Analysis Method Based on Dynamic Convolution and 3D-Variation
Predictive auxiliary objectives in deep RL mimic learning in the brain
Adaptive Camera Sensor for Vision Models
Bootstrapping Language Models with DPO Implicit Rewards
Texttovec: Deep Contextualized Neural autoregressive Topic Models of Language with Distributed Compositional Prior
Automated Self-Supervised Learning for Graphs
AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution
Adversarial Support Alignment
Unsupervised Object Keypoint Learning using Local Spatial Predictability
InstantSwap: Fast Customized Concept Swapping across Sharp Shape Differences
Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization
FeedFace: Efficient Inference-based Face Personalization via Diffusion Models
Learning Domain-Agnostic Representation for Disease Diagnosis
CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs
Domain-Robust Visual Imitation Learning with Mutual Information Constraints
MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations
Talk like a Graph: Encoding Graphs for Large Language Models
Optimized Multi-Token Joint Decoding With Auxiliary Model for LLM Inference
Getting a CLUE: A Method for Explaining Uncertainty Estimates
Conservative Safety Critics for Exploration
LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion Models
W-PCA Based Gradient-Free Proxy for Efficient Search of Lightweight Language Models
Out-of-class novelty generation: an experimental foundation
Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge
BitStack: Any-Size Compression of Large Language Models in Variable Memory Environments
Feature-aligned N-BEATS with Sinkhorn divergence
CoCon: A Self-Supervised Approach for Controlled Text Generation
Delta-AI: Local objectives for amortized inference in sparse graphical models
AttEXplore: Attribution for Explanation with model parameters eXploration
Iterative Patch Selection for High-Resolution Image Recognition
Towards an automatic Turing test: Learning to evaluate dialogue responses
Aligners: Decoupling LLMs and Alignment
Making Sense of Reinforcement Learning and Probabilistic Inference
Boost then Convolve: Gradient Boosting Meets Graph Neural Networks
Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels
MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training
Emergence of functional and structural properties of the head direction system by optimization of recurrent neural networks
One Important Thing To Do Before Federated Training
Relational Multi-Task Learning: Modeling Relations between Data and Tasks
Learning To Explore Using Active Neural SLAM
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning
Transformer Block Coupling and its Correlation with Generalization in LLMs
Coupled Multiwavelet Operator Learning for Coupled Differential Equations
Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
Deep Reinforcement Learning Meets Structured Prediction, ICLR 2019 Workshop, New Orleans, Louisiana, United States, May 6, 2019
Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness
PETRA: Parallel End-to-end Training with Reversible Architectures
DaxBench: Benchmarking Deformable Object Manipulation with Differentiable Physics
LipSim: A Provably Robust Perceptual Similarity Metric
Probabilistic Conformal Prediction with Approximate Conditional Validity
Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature Finetuning
Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework
HERO: Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuning
Statistical Inference for Fisher Market Equilibrium
Improving the Generalization of Adversarial Training with Domain Adaptation
GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks
A global convergence theory for deep ReLU implicit networks via over-parameterization
Directional Message Passing for Molecular Graphs
Adaptive Pruning of Pretrained Transformer via Differential Inclusions
Confidential-DPproof: Confidential Proof of Differentially Private Training
Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?
On the Posterior Distribution in Denoising: Application to Uncertainty Quantification
Learning Graph Invariance by Harnessing Spuriosity
PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-agent Tasks
Intelligent Switching for Reset-Free RL
X-Drive: Cross-modality Consistent Multi-Sensor Data Synthesis for Driving Scenarios
Chain-of-Thought Provably Enables Learning the (Otherwise) Unlearnable
Multiscale Positive-Unlabeled Detection of AI-Generated Texts
Learning to Act from Actionless Videos through Dense Correspondences
H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection
Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning
Integral Performance Approximation for Continuous-Time Reinforcement Learning Control
Decomposing Causality and Fairness
CausalRivers - Scaling up benchmarking of causal discovery for real-world time-series
Measuring CLEVRness: Black-box Testing of Visual Reasoning Models
Towards Interpreting Visual Information Processing in Vision-Language Models
Mixed-Features Vectors and Subspace Splitting
OmniBind: Large-scale Omni Multimodal Representation via Binding Spaces
An Effective Theory of Bias Amplification
On Targeted Manipulation and Deception when Optimizing LLMs for User Feedback
The Polarised Regime of identifiable Variational Autoencoders
Chunked Autoregressive GAN for Conditional Waveform Synthesis
EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Mechanism and Emergence of Stacked Attention Heads in Multi-Layer Transformers
TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics
Temporal Difference Learning: Why It Can Be Fast and How It Will Be Faster
Unified Discrete Diffusion for Simultaneous Vision-Language Generation
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
Kernel Implicit Variational Inference
Modality-Specialized Synergizers for Interleaved Vision-Language Generalists
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning
Boundary Seeking GANs
EcoFace: Audio-Visual Emotional Co-Disentanglement Speech-Driven 3D Talking Face Generation
Learning to reason over visual objects
Restructuring Vector Quantization with the Rotation Trick
Backtracking Improves Generation Safety
ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction
Animate-X: Universal Character Image Animation with Enhanced Motion Representation
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention
Dropout-Based Rashomon Set Exploration for Efficient Predictive Multiplicity Estimation
R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference
Pre-training with Synthetic Data Helps Offline Reinforcement Learning
The Effects of Invertibility on the Representational Complexity of Encoders in Variational Autoencoders
Large Language Models Assume People are More Rational than We Really are
Linear Mode Connectivity in Differentiable Tree Ensembles
BrainOOD: Out-of-distribution Generalizable Brain Network Analysis
Epitopological learning and Cannistraci-Hebb network shape intelligence brain-inspired theory for ultra-sparse advantage in deep learning
DeciMamba: Exploring the Length Extrapolation Potential of Mamba
Generative STResnet for Crime Prediction
PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees
LOIRE: LifelOng learning on Incremental data via pre-trained language model gRowth Efficiently
Towards General-Purpose Model-Free Reinforcement Learning
Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer
Simple and efficient architecture search for Convolutional Neural Networks
Large-width functional asymptotics for deep Gaussian neural networks
Spatially Structured Recurrent Modules
Revisiting Data Augmentation in Deep Reinforcement Learning
Learning to Generate Diverse Pedestrian Movements from Web Videos with Noisy Labels
Identity Crisis: Memorization and Generalization Under Extreme Overparameterization
An Image Is Worth 1000 Lies: Transferability of Adversarial Images across Prompts on Vision-Language Models
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods
Interpreting the Second-Order Effects of Neurons in CLIP
Learning Safe Multi-agent Control with Decentralized Neural Barrier Certificates
OmniSep: Unified Omni-Modality Sound Separation with Query-Mixup
Neural Stored-program Memory
Ridge Regression: Structure, Cross-Validation, and Sketching
Advancing Graph Generation through Beta Diffusion
Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling
On the role of population heterogeneity in emergent communication
Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization
Almost Linear Constant-Factor Sketching for $\ell_1$ and Logistic Regression
Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
Delta: Deep Learning Transfer using Feature Map with Attention for Convolutional Networks
Wayward Concepts In Multimodal Models
Maximum Entropy Heterogeneous-Agent Reinforcement Learning
Holistic Adversarially Robust Pruning
Are Transformers universal approximators of sequence-to-sequence functions?
ManiSkill-HAB: A Benchmark for Low-Level Manipulation in Home Rearrangement Tasks
Variance-Reducing Couplings for Random Features
AdaMerging: Adaptive Model Merging for Multi-Task Learning
LaMP: Language-Motion Pretraining for Motion Generation, Retrieval, and Captioning
Is Attention Better Than Matrix Decomposition?
Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples
{τ}-bench: A Benchmark for \underline{T}ool-\underline{A}gent-\underline{U}ser Interaction in Real-World Domains
AFlow: Automating Agentic Workflow Generation
Hierarchical Sliced Wasserstein Distance
Assessing Generalization of SGD via Disagreement
Spatial-Mamba: Effective Visual State Space Models via Structure-Aware State Fusion
Parameter-Based Value Functions
Trigger Hunting with a Topological Prior for Trojan Detection
MovingParts: Motion-based 3D Part Discovery in Dynamic Radiance Field
Inductive Matrix Completion Based on Graph Neural Networks
FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference
For self-supervised learning, Rationality implies generalization, provably
Solving Inverse Problems in Medical Imaging with Score-Based Generative Models
Streamlining Redundant Layers to Compress Large Language Models
Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space
GPAvatar: Generalizable and Precise Head Avatar from Image(s)
AIR-BENCH 2024: A Safety Benchmark based on Regulation and Policies Specified Risk Categories
On the Impossibility of Global Convergence in Multi-Loss Optimization
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks
Collapse by Conditioning: Training Class-conditional GANs with Limited Data
MECTA: Memory-Economic Continual Test-Time Model Adaptation
Knowledge Fusion of Large Language Models
On the Saturation Effect of Kernel Ridge Regression
Long-time asymptotics of noisy SVGD outside the population limit
Hyper-Decision Transformer for Efficient Online Policy Adaptation
Text-to-3D with Classifier Score Distillation
Actions Speak Louder Than Words: Rate-Reward Trade-off in Markov Decision Processes
Few-Shot Learning with Graph Neural Networks
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
Multi-Objective Online Learning
Learning to Estimate Shapley Values with Vision Transformers
Re-Aligning Language to Visual Objects with an Agentic Workflow
Trajectory attention for fine-grained video motion control
On the Expressiveness of Rational ReLU Neural Networks With Bounded Depth
lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning
Set Learning for Accurate and Calibrated Models
Jointly-Learned Exit and Inference for a Dynamic Neural Network
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
PiCO: Peer Review in LLMs based on Consistency Optimization
Context Steering: Controllable Personalization at Inference Time
Planning with Large Language Models for Code Generation
Topology-Aware Segmentation Using Discrete Morse Theory
Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks
DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenes
Entity-Centric Reinforcement Learning for Object Manipulation from Pixels
HiGen: Hierarchical Graph Generative Networks
Composing Task Knowledge With Modular Successor Feature Approximators
Scalable Transfer Learning with Expert Models
RFMamba: Frequency-Aware State Space Model for RF-Based Human-Centric Perception
PTaRL: Prototype-based Tabular Representation Learning via Space Calibration
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Vector-ICL: In-context Learning with Continuous Vector Representations
Function-space Parameterization of Neural Networks for Sequential Learning
Hierarchical interpretations for neural network predictions
Reconciling Model Multiplicity for Downstream Decision Making
Planning Anything with Rigor: General-Purpose Zero-Shot Planning with LLM-based Formalized Programming
Few-shot Learning via Dirichlet Tessellation Ensemble
Long-tail learning via logit adjustment
Semi-Supervised Few-Shot Learning with MAML
Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods
Can In-context Learning Really Generalize to Out-of-distribution Tasks?
Alternating Differentiation for Optimization Layers
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization
Transformer Learns Optimal Variable Selection in Group-Sparse Classification
Future Language Modeling from Temporal Document History
A Theory of Usable Information under Computational Constraints
Learning to Generate 3D Shapes with Generative Cellular Automata
A Causal Lens for Learning Long-term Fair Policies
Generative Adversarial Learning of Markov Chains
Denoising Diffusion via Image-Based Rendering
Not All Heads Matter: A Head-Level KV Cache Compression Method with Integrated Retrieval and Reasoning
Stochastic Gradient Descent for Gaussian Processes Done Right
Answering Questions Over Knowledge Graphs Using Logic Programming Along with Language Models
Corrupted Image Modeling for Self-Supervised Visual Pre-Training
Learning Mixed-Curvature Representations in Product Spaces
Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series
Sparsely-Connected Neural Networks: Towards Efficient VLSI Implementation of Deep Neural Networks
AniSDF: Fused-Granularity Neural Surfaces with Anisotropic Encoding for High-Fidelity 3D Reconstruction
Dirichlet-based Uncertainty Calibration for Active Domain Adaptation
Constructing Orthogonal Convolutions in an Explicit Manner
Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion
Test-time Adaptation against Multi-modal Reliability Bias
Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints
Revisiting Nearest Neighbor for Tabular Data: A Deep Tabular Baseline Two Decades Later
Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
Explorations in Texture Learning
Interpretable Geometric Deep Learning via Learnable Randomness Injection
Mathematical Reasoning in Latent Space
HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models
Differentiable Rule Induction from Raw Sequence Inputs
On the Analysis of GAN-based Image-to-Image Translation with Gaussian Noise Injection
RESuM: A Rare Event Surrogate Model for Physics Detector Design
SALMONN: Towards Generic Hearing Abilities for Large Language Models
Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation
Generating CAD Code with Vision-Language Models for 3D Designs
On the Optimal Memorization Capacity of Transformers
Weighted Point Set Embedding for Multimodal Contrastive Learning Toward Optimal Similarity Metric
Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields
On Representing Mixed-Integer Linear Programs by Graph Neural Networks
Distilling Structural Representations into Protein Sequence Models
Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness
Multi-domain Distribution Learning for De Novo Drug Design
Interacting Contour Stochastic Gradient Langevin Dynamics
Few-shot Backdoor Attacks via Neural Tangent Kernels
BenTo: Benchmark Reduction with In-Context Transferability
Regularizing Energy among Training Samples for Out-of-Distribution Generalization
Hierarchical Reinforcement Learning by Discovering Intrinsic Options
Distilling GANs with Style-Mixed Triplets for X2I Translation with Limited Data
BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models
MMTEB: Massive Multilingual Text Embedding Benchmark
Emergent Communication through Negotiation
Revelio: Interpretable Long-Form Question Answering
Hyperbolic Attention Networks
Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework
RRM: Robust Reward Model Training Mitigates Reward Hacking
Autoregressive Entity Retrieval
CAX: Cellular Automata Accelerated in JAX
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
An Unconstrained Layer-Peeled Perspective on Neural Collapse
Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
Certifying Some Distributional Robustness with Principled Adversarial Training
ViBiDSampler: Enhancing Video Interpolation Using Bidirectional Diffusion Sampler
Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs
Self-supervised Learning is More Robust to Dataset Imbalance
Stealthy Shield Defense: A Conditional Mutual Information-Based Approach against Black-Box Model Inversion Attacks
Efficient Active Search for Combinatorial Optimization Problems
Federated Domain Generalization with Data-free On-server Matching Gradient
Implicit Neural Representation Inference for Low-Dimensional Bayesian Deep Learning
Calibration tests beyond classification
Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning
Differential learning kinetics govern the transition from memorization to generalization during in-context learning
Learning to Induce Causal Structure
Unifying Likelihood-free Inference with Black-box Optimization and Beyond
Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients
LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer
Unveiling Options with Neural Network Decomposition
LLaVA-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models
Spikformer: When Spiking Neural Network Meets Transformer
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
A Statistical Framework for Efficient Out of Distribution Detection in Deep Neural Networks
IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation
Parameter and Data Efficient Spectral Style-DCGAN
TIPS: Text-Image Pretraining with Spatial awareness
Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models
Representation Degeneration Problem in Training Natural Language Generation Models
Efficient and Information-Preserving Future Frame Prediction and Beyond
Which Layer is Learning Faster? A Systematic Exploration of Layer-wise Convergence Rate for Deep Neural Networks
Beyond Canonicalization: How Tensorial Messages Improve Equivariant Message Passing
Consistency Models Made Easy
Latent Radiance Fields with 3D-aware 2D Representations
dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation
BECLR: Batch Enhanced Contrastive Few-Shot Learning
Mastering Task Arithmetic: τJp as a Key Indicator for Weight Disentanglement
Quantum Algorithms for Deep Convolutional Neural Networks
Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods
Enhancing Language Models for Financial Relation Extraction with Named Entities and Part-of-Speech
Small-scale proxies for large-scale Transformer training instabilities
TextShield: Beyond Successfully Detecting Adversarial Sentences in text classification
Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization
Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums
RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation
Constraint-Conditioned Actor-Critic for Offline Safe Reinforcement Learning
A Second-Order Perspective on Model Compositionality and Incremental Learning
SGDA with shuffling: faster convergence for nonconvex-PŁ minimax optimization
Adaptive Procedural Task Generation for Hard-Exploration Problems
Extrapolation and learning equations
Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs
Unsupervised Control Through Non-Parametric Discriminative Rewards
Exposure Bracketing Is All You Need For A High-Quality Image
McEval: Massively Multilingual Code Evaluation
Permutation-Based SGD: Is Random Optimal?
γ-MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models
Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer
On Bridging Generic and Personalized Federated Learning for Image Classification
Inductive Relation Prediction Using Analogy Subgraph Embeddings
PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method
EDCDE - Extended Discovery of Closed-Form Differential Equations
POPGym: Benchmarking Partially Observable Reinforcement Learning
Interpreting CLIP's Image Representation via Text-Based Decomposition
Distributionally Robust Optimization with Bias and Variance Reduction
The Hidden Cost of Waiting for Accurate Predictions
Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering
Unbiased Watermark for Large Language Models
Simple, Good, Fast: Self-Supervised World Models Free of Baggage
Controllable Safety Alignment: Inference-Time Adaptation to Diverse Safety Requirements
Fast Adaptation in Generative Models with Generative Matching Networks