yusuke1997/dblp-id-title huggingface dataset:
SleepSMC: Ubiquitous Sleep Staging via Supervised Multimodal Coordination
Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy
TUVF: Learning Generalizable Texture UV Radiance Fields
Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification
Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance
Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation
π2vec: Policy Representation with Successor Features
Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving
Generating Natural Adversarial Examples
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Incorporating Visual Correspondence into Diffusion Model for Virtual Try-On
Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform
Data Center Cooling System Optimization Using Offline Reinforcement Learning
Dataset Meta-Learning from Kernel Ridge-Regression
Adaptive Optimization in the ∞-Width Limit
Jailbreaking as a Reward Misspecification Problem
Leveraging Variable Sparsity to Refine Pareto Stationarity in Multi-Objective Optimization
Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize
Deep Variational Information Bottleneck
Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control
Alt-Text with Context: Improving Accessibility for Images on Twitter
MIA-DPO: Multi-Image Augmented Direct Preference Optimization For Large Vision-Language Models
Voxurf: Voxel-based Efficient and Accurate Neural Surface Reconstruction
Content-Style Learning from Unaligned Domains: Identifiability under Unknown Latent Dimensions
Can discrete information extraction prompts generalize across language models?
Learning Deep Latent-variable MRFs with Amortized Bethe Free Energy Minimization
Non-parametric Outlier Synthesis
Balancing Constraints and Rewards with Meta-Gradient D4PG
ImDy: Human Inverse Dynamics from Imitated Observations
StyleNeRF: A Style-based 3D Aware Generator for High-resolution Image Synthesis
How to deal with missing data in supervised deep learning?
Visually-Augmented Language Modeling
Can Transformers Capture Spatial Relations between Objects?
Universal Jailbreak Backdoors from Poisoned Human Feedback
Learning Subgoal Representations with Slow Dynamics
Policy Gradient for Reinforcement Learning with General Utilities
Scalable Influence and Fact Tracing for Large Language Model Pretraining
Program Synthesis for Character Level Language Modeling
Cross-lingual Alignment vs Joint Training: A Comparative Study and A Simple Unified Framework
MAML is a Noisy Contrastive Learner in Classification
Implicit Maximum a Posteriori Filtering via Adaptive Optimization
Contextual Transformation Networks for Online Continual Learning
Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Sequential Games
CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models
BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping
Continual Learning with Recursive Gradient Optimization
The Point to Which Soft Actor-Critic Converges
Wandering within a world: Online contextualized few-shot learning
Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient
A recurrent neural network without chaos
A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation
DINO: A Conditional Energy-Based GAN for Domain Translation
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients
Intervening Anchor Token: Decoding Strategy in Alleviating Hallucinations for MLLMs
Towards Verified Robustness under Text Deletion Interventions
Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications
Effective and Efficient Time-Varying Counterfactual Prediction with State-Space Models
SWE-bench: Can Language Models Resolve Real-world Github Issues?
Solving stochastic weak Minty variational inequalities without increasing batch size
Not-So-Optimal Transport Flows for 3D Point Cloud Generation
Knowledge Distillation based Degradation Estimation for Blind Super-Resolution
ADBM: Adversarial Diffusion Bridge Model for Reliable Adversarial Purification
OTOv2: Automatic, Generic, User-Friendly
Graph inference learning for semi-supervised classification
Query-based Knowledge Transfer for Heterogeneous Learning Environments
Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies
Learning to superoptimize programs
Feature Collapse
Learning Thresholds with Latent Values and Censored Feedback
LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures
A System for Morphology-Task Generalization via Unified Representation and Behavior Distillation
Quality Measures for Dynamic Graph Generative Models
SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore
Optimal Transport Maps For Distribution Preserving Operations on Latent Spaces of Generative Models
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic
Dynamic Model Pruning with Feedback
Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
AgentRefine: Enhancing Agent Generalization through Refinement Tuning
Optimizing Spca-based Continual Learning: A Theoretical Approach
SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training
IterGen: Iterative Semantic-aware Structured LLM Generation with Backtracking
R2-Guard: Robust Reasoning Enabled LLM Guardrail via Knowledge-Enhanced Logical Reasoning
A Formal Framework for Understanding Length Generalization in Transformers
Meta-Learning for Semi-Supervised Few-Shot Classification
Tuformer: Data-driven Design of Transformers for Improved Generalization or Efficiency
Using Language to Extend to Unseen Domains
NeRM: Learning Neural Representations for High-Framerate Human Motion Synthesis
On the Role of Attention Heads in Large Language Model Safety
Aioli: A Unified Optimization Framework for Language Model Data Mixing
Temporal Flexibility in Spiking Neural Networks: Towards Generalization Across Time Steps and Deployment Friendliness
A Hierarchical Model for Device Placement
STORM: Spatio-TempOral Reconstruction Model For Large-Scale Outdoor Scenes
Fast Uncovering of Protein Sequence Diversity from Structure
Scaling In-the-Wild Training for Diffusion-based Illumination Harmonization and Editing by Imposing Consistent Light Transport
Learning Execution through Neural Code fusion
From Models to Microtheories: Distilling a Model's Topical Knowledge for Grounded Question-Answering
Borderline Sample Extraction from a Trained Classifier
A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Efficient stagewise pretraining via progressive subnetworks
Realistic Evaluation of Deep Partial-Label Learning Algorithms
Fine-grained Differentiable Physics: A Yarn-level Model for Fabrics
Learning LLM-as-a-Judge for Preference Alignment
Hindsight: Posterior-guided training of retrievers for improved open-ended generation
DP-SGD Without Clipping: The Lipschitz Neural Network Way
Bilinear MLPs enable weight-based mechanistic interpretability
What Should Not Be Contrastive in Contrastive Learning
SANA: Efficient High-Resolution Text-to-Image Synthesis with Linear Diffusion Transformers
Black-Box Detection of Language Model Watermarks
Sound and Complete Neural Network Repair with Minimality and Locality Guarantees
How to Verify Any (Reasonable) Distribution Property: Computationally Sound Argument Systems for Distributions
SOO-Bench: Benchmarks for Evaluating the Stability of Offline Black-Box Optimization
Multi-Level Local SGD: Distributed SGD for Heterogeneous Hierarchical Networks
Learning Curve Prediction with Bayesian Neural Networks
Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse
Is attention required for ICL? Exploring the Relationship Between Model Architecture and In-Context Learning Ability
Regularized Inverse Reinforcement Learning
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
Optimality of Matrix Mechanism on ℓpp-metric
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations
Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge
Improved sampling via learned diffusions
On the Convergence of AdaGrad(Norm) on ℝ d : Beyond Convexity, Non-Asymptotic Rate and Acceleration
Lifting Architectural Constraints of Injective Flows
Non-myopic Generation of Language Models for Reasoning and Planning
Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits
ParaSolver: A Hierarchical Parallel Integral Solver for Diffusion Models
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How
SoftEDA: Rethinking Rule-Based Data Augmentation with Soft Labels
Generative Augmented Flow Networks
U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models
Neural Module Networks for Reasoning over Text
Recurrent Normalization Propagation
Policy Design in Long-run Welfare Dynamics
Multi-Source Diffusion Models for Simultaneous Music Generation and Separation
Langevin Soft Actor-Critic: Efficient Exploration through Uncertainty-Driven Critic Learning
Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning
Solving hidden monotone variational inequalities with surrogate losses
Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
A Good Learner can Teach Better: Teacher-Student Collaborative Knowledge Distillation
Synthetic Gradient Methods with Virtual Forward-Backward Networks
Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space
MMAD: A Comprehensive Benchmark for Multimodal Large Language Models in Industrial Anomaly Detection
On Quantizing Neural Representation for Variable-Rate Video Coding
Adverb Is the Key: Simple Text Data Augmentation with Adverb Deletion
Preference Diffusion for Recommendation
Wasserstein-2 Generative Networks
Learning Evolving Tools for Large Language Models
A Recipe for Improved Certifiable Robustness
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling
Mutual Effort for Efficiency: A Similarity-based Token Pruning for Vision Transformers in Self-Supervised Learning
LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation
Video In-context Learning: Autoregressive Transformers are Zero-Shot Video Imitators
Generative Representational Instruction Tuning
Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions
FusionNet: Fusing via Fully-aware Attention with Application to Machine Comprehension
VICtoR: Learning Hierarchical Vision-Instruction Correlation Rewards for Long-horizon Manipulation
Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization
Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings
Gradient Matching for Domain Generalization
On the Usefulness of Embeddings, Clusters and Strings for Text Generation Evaluation
Language-driven Semantic Segmentation
Concept Bottleneck Generative Models
Weighted Ensemble Self-Supervised Learning
Facing the Elephant in the Room: Visual Prompt Tuning or Full finetuning?
Bayesian Meta Sampling for Fast Uncertainty Adaptation
Regularization Neural Networks via Constrained Virtual Movement Field
Neural graphical modelling in continuous-time: consistency guarantees and algorithms
Generative Planning for Temporally Coordinated Exploration in Reinforcement Learning
Environmental drivers of systematicity and generalization in a situated agent
Tree-Structured Attention with Hierarchical Accumulation
Guiding Safe Exploration with Weakest Preconditions
Language Models can do Zero-Shot Visual Referring Expression Comprehension
DMBP: Diffusion model-based predictor for robust offline reinforcement learning against state observation perturbations
Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm
Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory
Towards Continuous Reuse of Graph Models via Holistic Memory Diversification
CoMPS: Continual Meta Policy Search
Recovering Manifold Structure Using Ollivier Ricci Curvature
Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling
DiffGANPaint: Fast Inpainting Using Denoising Diffusion GANs
MARS: Meta-learning as Score Matching in the Function Space
Effective Interplay between Sparsity and Quantization: From Theory to Practice
Statistical Property Testing for Generative Models
DynaMS: Dyanmic Margin Selection for Efficient Deep Learning
Geometry of Polysemy
FlowDec: A flow-based full-band general audio codec with high perceptual quality
Learning Hierarchical Image Segmentation For Recognition and By Recognition
On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning
Can Video LLMs Refuse to Answer? Alignment for Answerability in Video Large Language Models
DARTS-: Robustly Stepping out of Performance Collapse Without Indicators
Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers
Fast And Slow Learning Of Recurrent Independent Mechanisms
Continuously Discovering Novel Strategies via Reward-Switching Policy Optimization
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP
Fast Generation for Convolutional Autoregressive Models
SKILL-MIX: a Flexible and Expandable Family of Evaluations for AI Models
Optimal Transport for Time Series Imputation
NECO: NEural Collapse Based Out-of-distribution detection
Robust Similarity Learning with Difference Alignment Regularization
Uni-Sign: Toward Unified Sign Language Understanding at Scale
Knowledge Flow: Improve Upon Your Teachers
Sensitivity and Generalization in Neural Networks: an Empirical Study
On Mutual Information Maximization for Representation Learning
Universal generalization guarantees for Wasserstein distributionally robust models
QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension
Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning
The mechanistic basis of data dependence and abrupt learning in an in-context classification task
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
Brain-inspired Lp-Convolution benefits large kernels and aligns better with visual cortex
Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics
Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation
Exploring perceptual straightness in learned visual representations
On the Feature Learning in Diffusion Models
Enhancing Robust Fairness via Confusional Spectral Regularization
Provable Uncertainty Decomposition via Higher-Order Calibration
Overcoming Catastrophic Interference using Conceptor-Aided Backpropagation
Learning Factorized Representations for Open-Set Domain Adaptation
Knowledge Distillation Through Time For Future Event Prediction
Learning Fair Graph Representations via Automated Data Augmentations
Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning
Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness
Who Is Your Right Mixup Partner in Positive and Unlabeled Learning
Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributions
Better than Your Teacher: LLM Agents that learn from Privileged AI Feedback
SelectFormer in Data Markets: Privacy-Preserving and Efficient Data Selection for Transformers with Multi-Party Computation
Advancing Radiograph Representation Learning with Masked Record Modeling
A Hierarchical Bayesian Model for Few-Shot Meta Learning
Sailing Through Spectra: Unveiling the Potential of Multi-Spectral Information in Marine Debris Segmentation
White Noise Analysis of Neural Networks
Predict Responsibly: Increasing Fairness by Learning to Defer
GTMGC: Using Graph Transformer to Predict Molecule's Ground-State Conformation
Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks
Towards Certification of Uncertainty Calibration under Adversarial Attacks
Towards Stochastic Gradient Variance Reduction by Solving a Filtering Problem
TANGO: Co-Speech Gesture Video Reenactment with Hierarchical Audio Motion Embedding and Diffusion Interpolation
Infinite-Resolution Integral Noise Warping for Diffusion Models
Privacy-Preserving In-Context Learning for Large Language Models
DisPose: Disentangling Pose Guidance for Controllable Human Image Animation
AlphaZero-based Proof Cost Network to Aid Game Solving
TRAM: Bridging Trust Regions and Sharpness Aware Minimization
Learning Invariant Representations for Reinforcement Learning without Reconstruction
Provable Reward-Agnostic Preference-Based Reinforcement Learning
VideoPhy: Evaluating Physical Commonsense for Video Generation
SQA3D: Situated Question Answering in 3D Scenes
Revealing the 3D Cosmic Web through Gravitationally Constrained Neural Fields
Neural network parameter regression for lattice quantum chromodynamics simulations in nuclear and particle physics
Glimpse: Enabling White-Box Methods to Use Proprietary Models for Zero-Shot LLM-Generated Text Detection
MMFakeBench: A Mixed-Source Multimodal Misinformation Detection Benchmark for LVLMs
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training
Minimum Width for Universal Approximation
When Do Curricula Work?
Learning Robust Generalizable Radiance Field with Visibility and Feature Augmented Point Representation
On the regularization of Wasserstein GANs
Modeling the Second Player in Distributionally Robust Optimization
DAMO: Decoding by Accumulating Activations Momentum for Mitigating Hallucinations in Vision-Language Models
Learning Dynamics of LLM Finetuning
Multi-Agent Interactions Modeling with Correlated Policies
SePer: Measure Retrieval Utility Through The Lens Of Semantic Perplexity Reduction
Thought Propagation: an Analogical Approach to Complex Reasoning with Large Language Models
Unsupervised Cross-Domain Image Generation
Multi-Scale Dense Networks for Resource Efficient Image Classification
Emoji Kitchen with Controlled Fusion
RandProx: Primal-Dual Optimization Algorithms with Randomized Proximal Updates
MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine
How Informative is the Approximation Error from Tensor Decomposition for Neural Network Compression?
Adaptive Gradient Methods with Dynamic Bound of Learning Rate
CrossLoco: Human Motion Driven Control of Legged Robots via Guided Unsupervised Reinforcement Learning
Hard ASH: Sparsity and the right optimizer make a continual learner
Post-hoc Concept Bottleneck Models
Animate Your Thoughts: Reconstruction of Dynamic Natural Vision from Human Brain Activity
Effect of Activation Functions on the Training of Overparametrized Neural Nets
Diffusion On Syntax Trees For Program Synthesis
Online GNN Evaluation Under Test-time Graph Distribution Shifts
KBLaM: Knowledge Base augmented Language Model
Task-Aware Information Routing from Common Representation Space in Lifelong Learning
Uncovering Bias: Exploring Gender Dynamics in Distance-Aware Mixup Techniques
State Space Models are Provably Comparable to Transformers in Dynamic Token Selection
Curriculum-based Co-design of Morphology and Control of Voxel-based Soft Robots
Quality over Quantity in Attention Layers: When Adding More Heads Hurts
Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning
NASI: Label- and Data-agnostic Neural Architecture Search at Initialization
GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems
The Implicit Bias of Minima Stability in Multivariate Shallow ReLU Networks
EX-Graph: A Pioneering Dataset Bridging Ethereum and X
Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics
Light Schrödinger Bridge
Integrating Categorical Semantics into Unsupervised Domain Translation
The Devil is in the Object Boundary: Towards Annotation-free Instance Segmentation using Foundation Models
Linear attention is (maybe) all you need (to understand Transformer optimization)
Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections
Improving GAN Training via Binarized Representation Entropy (BRE) Regularization
Explicitly Stating Assumptions Reduces Hallucinations in Natural Language Inference
Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout
Pseudo Numerical Methods for Diffusion Models on Manifolds
A Generalist Hanabi Agent
Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them
Mega: Moving Average Equipped Gated Attention
A Graph Enhanced Symbolic Discovery Framework For Efficient Logic Optimization
Unsupervised Meta-Learning via In-Context Learning
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems
Deep Variational Implicit Processes
Learning to live with Dale's principle: ANNs with separate excitatory and inhibitory units
Noise Map Guidance: Inversion with Spatial Context for Real Image Editing
NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation
ESE: Espresso Sentence Embeddings
How Much is Unseen Depends Chiefly on Information About the Seen
GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking
Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits
Crystal Diffusion Variational Autoencoder for Periodic Material Generation
Domain-Agnostic Molecular Generation with Chemical Feedback
Mirror-Generative Neural Machine Translation
Adversarial Machine Learning at Scale
A Framework for the Quantitative Evaluation of Disentangled Representations
Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series
Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees
The Importance of Pessimism in Fixed-Dataset Policy Optimization
Performance guarantees for transferring representations
Fine-Tuning Language Models for Factuality
Hebbian Deep Learning Without Feedback
F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization
Model-Based Offline Planning
Weakly-Supervised Affordance Grounding Guided by Part-Level Semantic Priors
FedWon: Triumphing Multi-domain Federated Learning Without Normalization
Systematic Outliers in Large Language Models
Knowing Your Target: Target-Aware Transformer Makes Better Spatio-Temporal Video Grounding
Growth Inhibitors for Suppressing Inappropriate Image Concepts in Diffusion Models
Incorporating Expert Prior Knowledge for Oral Lesion Recognition
The role of over-parametrization in generalization of neural networks
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
Three Mechanisms of Weight Decay Regularization
Benchmarking and Improving Generator-Validator Consistency of Language Models
InstaRevive: One-Step Image Enhancement via Dynamic Score Matching
Monotonic Kronecker-Factored Lattice
PairNorm: Tackling Oversmoothing in GNNs
A Graph Neural Network Approach to Automated Model Building in Cryo-EM Maps