yusuke1997/dblp-id-title huggingface dataset:
Reducing Hallucinations in Large Vision-Language Models via Latent Space Steering
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks
Solving Video Inverse Problems Using Image Diffusion Models
Federated Learning from Only Unlabeled Data with Class-conditional-sharing Clients
On the Quantitative Analysis of Decoder-Based Generative Models
Outcome-directed Reinforcement Learning by Uncertainty \& Temporal Distance-Aware Curriculum Goal Generation
Visual Haystacks: A Vision-Centric Needle-In-A-Haystack Benchmark
Risk-Aware Reinforcement Learning with Coherent Risk Measures and Non-linear Function Approximation
CViT: Continuous Vision Transformer for Operator Learning
Disentanglement Analysis with Partial Information Decomposition
Hallucination Benchmark in Medical Visual Question Answering
AdaFisher: Adaptive Second Order Optimization via Fisher Information
CAMEx: Curvature-aware Merging of Experts
SGD Can Converge to Local Maxima
Training Transition Policies via Distribution Matching for Complex Tasks
Towards Bridging Generalization and Expressivity of Graph Neural Networks
PhysPDE: Rethinking PDE Discovery and a Physical Hypothesis Selection Benchmark
Reinforcement Learning on Web Interfaces using Workflow-Guided Exploration
Locality-Aware Graph Rewiring in GNNs
Enabling Lanuguage Models to Implicitly Learn Self-Improvement
BodyGen: Advancing Towards Efficient Embodiment Co-Design
CLEX: Continuous Length Extrapolation for Large Language Models
Scaling Convex Neural Networks with Burer-Monteiro Factorization
VideoShield: Regulating Diffusion-based Video Generation Models via Watermarking
Beyond the convexity assumption: Realistic tabular data generation under quantifier-free real linear constraints
Duolando: Follower GPT with Off-Policy Reinforcement Learning for Dance Accompaniment
High-dimensional SGD aligns with emerging outlier eigenspaces
Understanding Label Bias in Single Positive Multi-Label Learning
Controllable Blur Data Augmentation Using 3D-Aware Motion Estimation
Plug and Play Language Models: A Simple Approach to Controlled Text Generation
Unsupervised Vision-Language Grammar Induction with Shared Structure Modeling
Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise
Enhance Multi-View Classification Through Multi-Scale Alignment and Expanded Boundary
Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks
The Need for Speed: Pruning Transformers with One Recipe
Reversible Column Networks
Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control
Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs
Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
Controlling the Complexity and Lipschitz Constant improves Polynomial Nets
SketchKnitter: Vectorized Sketch Generation with Diffusion Models
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness Against Adversarial Attacks
Learning from Protein Structure with Geometric Vector Perceptrons
Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation
Embodied Active Defense: Leveraging Recurrent Feedback to Counter Adversarial Patches
Generalization Through the Lens of Leave-One-Out Error
Disentangling Representations through Multi-task Learning
Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds
Free Hunch: Denoiser Covariance Estimation for Diffusion Models Without Extra Costs
GraphCodeBERT: Pre-training Code Representations with Data Flow
Structured Object-Aware Physics Prediction for Video Modeling and Planning
Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable?
Adaptive and Generative Zero-Shot Learning
Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text
Training Neural Networks as Recognizers of Formal Languages
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
Dynamic Negative Guidance of Diffusion Models
A Closer Look at Few-shot Classification
Large-Vocabulary 3D Diffusion Model with Transformer
Group Preference Optimization: Few-Shot Alignment of Large Language Models
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks
Boltzmann Semantic Score: A Semantic Metric for Evaluating Large Vision Models Using Large Language Models
FedBABU: Toward Enhanced Representation for Federated Image Classification
Hybrid Sharing for Multi-Label Image Classification
Quamba: A Post-Training Quantization Recipe for Selective State Space Models
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications
ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities
Neural Approximate Mirror Maps for Constrained Diffusion Models
RAPID: Retrieval Augmented Training of Differentially Private Diffusion Models
Shedding Light on Time Series Classification using Interpretability Gated Networks
The Case for Cleaner Biosignals: High-fidelity Neural Compressor Enables Transfer from Cleaner iEEG to Noisier EEG
VideoWebArena: Evaluating Long Context Multimodal Agents with Video Understanding Web Tasks
Bias Propagation in Federated Learning
Learning Prototype-oriented Set Representations for Meta-Learning
Multi-Dimensional Conformal Prediction
Denoising Diffusion Implicit Models
PersonalLLM: Tailoring LLMs to Individual Preferences
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
Boosting Multiagent Reinforcement Learning via Permutation Invariant and Permutation Equivariant Networks
Gramian Multimodal Representation Learning and Alignment
Affinity-based Homophily: Can we measure homophily of a graph without using node labels?
Statistical inference for individual fairness
BRAID: Input-driven Nonlinear Dynamical Modeling of Neural-Behavioral Data
Differentially private optimization for non-decomposable objective functions
GO Gradient for Expectation-Based Objectives
Scalable Language Model with Generalized Continual Learning
Reward Dimension Reduction for Scalable Multi-Objective Reinforcement Learning
NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-end Learning and Control
Progressive Voronoi Diagram Subdivision Enables Accurate Data-free Class-Incremental Learning
Cross-Embodiment Dexterous Grasping with Reinforcement Learning
Bridging the Semantic Gap Between Text and Table: A Case Study on NL2SQL
You Only Need Adversarial Supervision for Semantic Image Synthesis
CKConv: Continuous Kernel Convolution For Sequential Data
COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits
Packed Ensembles for efficient uncertainty estimation
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities
On the Performance Analysis of Momentum Method: A Frequency Domain Perspective
SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection
Decentralized Optimization with Coupled Constraints
MMDisCo: Multi-Modal Discriminator-Guided Cooperative Diffusion for Joint Audio and Video Generation
A2BCD: Asynchronous Acceleration with Optimal Complexity
Real-Time Image Demoiréing on Mobile Devices
Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization
PhyMPGN: Physics-encoded Message Passing Graph Network for spatiotemporal PDE systems
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior
Emergence of foveal image sampling from learning to attend in visual scenes
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient
Is Self-Repair a Silver Bullet for Code Generation?
Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages
Lesion Search with Self-supervised Learning
Diffusion in Diffusion: Cyclic One-Way Diffusion for Text-Vision-Conditioned Generation
Minimax Curriculum Learning: Machine Teaching with Desirable Difficulties and Scheduled Diversity
Computing all Optimal Partial Transports
The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023
DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations
Explaining Temporal Graph Models through an Explorer-Navigator Framework
Distributional Meta-Gradient Reinforcement Learning
Independent-Set Design of Experiments for Estimating Treatment and Spillover Effects under Network Interference
AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models
Catastrophic Failure of LLM Unlearning via Quantization
Active Neural Localization
Visual prompting Methods for GPT-4V based Zero-Shot Graphic Layout Design Generation
Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning
Transferring Optimality Across Data Distributions via Homotopy Methods
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks
Fantastic Generalization Measures and Where to Find Them
Learning Features of Music From Scratch
Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation
Neural Implicit Shape Editing using Boundary Sensitivity
State-only Imitation with Transition Dynamics Mismatch
Efficiently Computing Similarities to Private Datasets
From Search to Sampling: Generative Models for Robust Algorithmic Recourse
See It from My Perspective: How Language Affects Cultural Bias in Image Understanding
Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration
DiffMimic: Efficient Motion Mimicking with Differentiable Physics
Geometric Transformers for Protein Interface Contact Prediction
Improving Differentiable Neural Computers Through Memory Masking, De-allocation, and Link Distribution Sharpness Control
Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching
TRGP: Trust Region Gradient Projection for Continual Learning
Robust estimation via Generative Adversarial Networks
Changing Model Behavior at Test-time Using Reinforcement Learning
Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning
Separating common from salient patterns with Contrastive Representation Learning
Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness
Negative Label Guided OOD Detection with Pretrained Vision-Language Models
PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters
Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness
Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing
Compressing Word Embeddings via Deep Compositional Code Learning
Improving Hyperspectral Adversarial Robustness Under Multiple Attacks
Large Language Models Can Be Strong Differentially Private Learners
On the approximation properties of recurrent encoder-decoder architectures
Emergence of a High-Dimensional Abstraction Phase in Language Transformers
On the Variance of the Adaptive Learning Rate and Beyond
Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions
Contextualizing biological perturbation experiments through language
Efficient Top-m Data Values Identification for Data Selection
LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading
Autoregressive Video Generation without Vector Quantization
Topology and Geometry of Half-Rectified Network Optimization
HiT-MDP: Learning the SMDP option framework on MDPs with Hidden Temporal Embeddings
Subtractive Mixture Models via Squaring: Representation and Learning
Is Synthetic Data from Generative Models Ready for Image Recognition?
Correlation and Navigation in the Vocabulary Key Representation Space of Language Models
ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQL
Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making
DINO as a von Mises-Fisher mixture model
Truncated Consistency Models
CREMA: Generalizable and Efficient Video-Language Reasoning via Multimodal Modular Fusion
How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations
BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games
Confidential-PROFITT: Confidential PROof of FaIr Training of Trees
Latent Bayesian Optimization via Autoregressive Normalizing Flows
Quasi-optimal Reinforcement Learning with Continuous Actions
Generative Principal Component Analysis
Unlocking Global Optimality in Bilevel Optimization: A Pilot Study
T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data
Learning Adaptive Multiresolution Transforms via Meta-Framelet-based Graph Convolutional Network
Synthetic Datasets for Neural Program Synthesis
SLTUNET: A Simple Unified Model for Sign Language Translation
i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning
Representation Deficiency in Masked Language Modeling
SweetDreamer: Aligning Geometric Priors in 2D diffusion for Consistent Text-to-3D
Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models
Meta-learning with differentiable closed-form solvers
One Hundred Neural Networks and Brains Watching Videos: Lessons from Alignment
Empowering Graph Representation Learning with Test-Time Graph Transformation
AIMS.au: A Dataset for the Analysis of Modern Slavery Countermeasures in Corporate Statements
H-GAP: Humanoid Control with a Generalist Planner
GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher
Population-size-Aware Policy Optimization for Mean-Field Games
Robust Overfitting may be mitigated by properly learned smoothening
OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation
Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning
CS-Bench: A Comprehensive Benchmark for Large Language Models towards Computer Science Mastery
Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games
Adversarial Machine Unlearning
Neural Speed Reading via Skim-RNN
Tree of Attributes Prompt Learning for Vision-Language Models
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
On the complexity of nonsmooth automatic differentiation
Zero-shot Imputation with Foundation Inference Models for Dynamical Systems
Concurrent Adversarial Learning for Large-Batch Training
Unprocessing Seven Years of Algorithmic Fairness
Learning to Schedule Communication in Multi-agent Reinforcement Learning
Strength Estimation and Human-Like Strength Adjustment in Games
Optimizing Neural Network Representations of Boolean Networks
Generalize Neural Network Through Smooth Hypothesis Function
FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks
An Unsupervised Deep Learning Approach for Real-World Image Denoising
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood
The Foundations of Tokenization: Statistical and Computational Concerns
Masked Completion via Structured Diffusion with White-Box Transformers
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning
Learning invariant representations of time-homogeneous stochastic dynamical systems
Efficient Continual Learning with Modular Networks and Task-Driven Priors
Negative Data Augmentation
Exo-Spacetimeformer: Time Series Prediction with External Forecast Integration
Learning explanations that are hard to vary
PolarNet: Learning to Optimize Polar Keypoints for Keypoint Based Object Detection
ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations
REvolve: Reward Evolution with Large Language Models using Human Feedback
Differentiable Trust Region Layers for Deep Reinforcement Learning
Federated Causal Discovery from Heterogeneous Data
Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion
GLAD: Learning Sparse Graph Recovery
Anomaly Detection for Tabular Data with Internal Contrastive Learning
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD
Dynamic Token Normalization improves Vision Transformers
Shape as Line Segments: Accurate and Flexible Implicit Surface Representation
The False Promise of Imitating Proprietary Language Models
Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time
HELMET: How to Evaluate Long-context Models Effectively and Thoroughly
Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation
Evaluating visual "common sense" using fine-grained classification and captioning tasks
ImpScore: A Learnable Metric For Quantifying The Implicitness Level of Sentences
Integrating Information from Natural Language Parse Tree to Code Generation
Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems
A Multi-Power Law for Loss Curve Prediction Across Learning Rate Schedules
Simplicial Embeddings in Self-Supervised Learning and Downstream Classification
DyCAST: Learning Dynamic Causal Structure from Time Series
RouteLLM: Learning to Route LLMs from Preference Data
Energy-based Backdoor Defense Against Federated Graph Learning
What do you learn from context? Probing for sentence structure in contextualized word representations
FILIP: Fine-grained Interactive Language-Image Pre-Training
AI Sandbagging: Language Models can Strategically Underperform on Evaluations
Effective post-training embedding compression via temperature control in contrastive training
Variational Intrinsic Control Revisited
MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data
Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference
Copyright-Protected Language Generation via Adaptive Model Fusion
Annealing Self-Distillation Rectification Improves Adversarial Training
Zero-CL: Instance and Feature decorrelation for negative-free symmetric contrastive learning
Arithmetic Without Algorithms: Language Models Solve Math with a Bag of Heuristics
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding
Sparsistency for inverse optimal transport
Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models
Targeted Hyperparameter Optimization with Lexicographic Preferences Over Multiple Objectives
L-Tuning: Synchronized Label Tuning for Prompt and Prefix in LLMS
Unsupervised Zero-Shot Reinforcement Learning via Dual-Value Forward-Backward Representation
ZeroDiff: Solidified Visual-semantic Correlation in Zero-Shot Learning
Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions
Aligned LLMs Are Not Aligned Browser Agents
All-but-the-Top: Simple and Effective Postprocessing for Word Representations
Delaunay Component Analysis for Evaluation of Data Representations
Generalized Natural Gradient Flows in Hidden Convex-Concave Games and GANs
Distance-Based Regularisation of Deep Networks for Fine-Tuning
ODE-based Smoothing Neural Network for Reinforcement Learning Tasks
Fine-tuning can Help Detect Pretraining Data from Large Language Models
Text Summarization with Oracle Expectation
Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions
How Gradient descent balances features: A dynamical analysis for two-layer neural networks
Top-Down Neural Model For Formulae
LEGO-Prover: Neural Theorem Proving with Growing Libraries
Critic Sequential Monte Carlo
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation
Chain-of-region: Visual Language Models Need Details for Diagram Analysis
Sub-policy Adaptation for Hierarchical Reinforcement Learning
Theory and Evaluation Metrics for Learning Disentangled Representations
Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models
Generative Pre-training for Speech with Flow Matching
Enhancing Human-AI Collaboration Through Logic-Guided Reasoning
Ward: Provable RAG Dataset Inference via LLM Watermarks
MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks
Learning the Uncertainty Set in Robust Markov Decision Process
InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective
Undistillable: Making A Nasty Teacher That CANNOT teach students
Measuring Forgetting of Memorized Training Examples
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
Beyond Categorical Label Representations for Image Classification
LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation
LARP: Tokenizing Videos with a Learned Autoregressive Generative Prior
Learning from Explanations with Neural Execution Tree
SE(3)-Equivariant Attention Networks for Shape Reconstruction in Function Space
Dream to Manipulate: Compositional World Models Empowering Robot Imitation Learning with Imagination
Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 Small
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
SelKD: Selective Knowledge Distillation via Optimal Transport Perspective
Beyond Next Token Prediction: Patch-Level Training for Large Language Models
NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals
Generative Models of Visually Grounded Imagination
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks
Safety Representations for Safer Policy Learning
Rephrase, Augment, Reason: Visual Grounding of Questions for Vision-Language Models
Plant 'n' Seek: Can You Find the Winning Ticket?
A Study on Sample Diversity in Generative Models: GANs vs. Diffusion Models
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound
Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward
Do WGANs succeed because they minimize the Wasserstein Distance? Lessons from Discrete Generators
SOREL: A Stochastic Algorithm for Spectral Risks Minimization
Knowledge and Attitude of Medical Students and Doctors towards Artificial Intelligence: A study of University of Ilorin
Neural Episodic Control with State Abstraction
Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning
(Mis)Fitting Scaling Laws: A Survey of Scaling Law Fitting Techniques in Deep Learning
Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design
Lemur: Harmonizing Natural Language and Code for Language Agents
Propagate Deeper and Adaptive Graph Convolutional Networks
CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothing
Neural Text Generation With Unlikelihood Training
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing
Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging
Meta-Learning with Latent Embedding Optimization
MisGAN: Learning from Incomplete Data with Generative Adversarial Networks
Adversarial Mixup Unlearning
Identity Matters in Deep Learning
DeFT: Decoding with Flash Tree-attention for Efficient Tree-structured LLM Inference
Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances
Risk Bounds of Accelerated SGD for Overparameterized Linear Regression
ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs
Large Language Models are Interpretable Learners
Open-ended VQA benchmarking of Vision-Language models by exploiting Classification datasets and their semantic hierarchy
Self-Supervised Continual Learning
SMART: Sentences as Basic Units for Text Evaluation
Bad-PFL: Exploiting Backdoor Attacks against Personalized Federated Learning