yusuke1997/dblp-id-title huggingface dataset:
Adding Conditional Control to Diffusion Models with Reinforcement Learning
Large Language Models Perform Diagnostic Reasoning
Robotouille: An Asynchronous Planning Benchmark for LLM Agents
3DIS: Depth-Driven Decoupled Image Synthesis for Universal Multi-Instance Generation
Higher-Order Graphon Neural Networks: Approximation and Cut Distance
Think-on-Graph 2.0: Deep and Faithful Large Language Model Reasoning with Knowledge-guided Retrieval Augmented Generation
Flow matching achieves almost minimax optimal convergence
BLEND: Behavior-guided Neural Population Dynamics Modeling via Privileged Knowledge Distillation
RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design
Contrastive Clustering to Mine Pseudo Parallel Data for Unsupervised Translation
Learning to Coordinate Manipulation Skills via Skill Behavior Diversification
Local Feature Swapping for Generalization in Reinforcement Learning
Certify or Predict: Boosting Certified Robustness with Compositional Architectures
Mitigating Adversarial Effects Through Randomization
One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation
Delta: Dense Efficient Long-Range 3D tracking for any video
SpeedyZero: Mastering Atari with Limited Data and Time
MQuAKE-Remastered: Multi-Hop Knowledge Editing Can Only Be Advanced with Reliable Evaluations
Reclaiming the Source of Programmatic Policies: Programmatic versus Latent Spaces
In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications
FlashMask: Efficient and Rich Mask Extension of FlashAttention
A Variational Inequality Perspective on Generative Adversarial Networks
Learning Protein Structure with a Differentiable Simulator
NOODL: Provable Online Dictionary Learning and Sparse Coding
Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference
Confidence Estimation Using Unlabeled Data
Factorized Fourier Neural Operators
Counterfactual Realizability
Hindsight PRIORs for Reward Learning from Human Preferences
Early Methods for Detecting Adversarial Images
FedFA: Federated Feature Augmentation
MADGEN: Mass-Spec attends to De Novo Molecular generation
Understanding Posterior Collapse in Generative Latent Variable Models
Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
LocoVR: Multiuser Indoor Locomotion Dataset in Virtual Reality
YouTube-SL-25: A Large-Scale, Open-Domain Multilingual Sign Language Parallel Corpus
Sqrt(d) Dimension Dependence of Langevin Monte Carlo
Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form
Continuous-Discrete Convolution for Geometry-Sequence Modeling in Proteins
UniGS: Unified Language-Image-3D Pretraining with Gaussian Splatting
Pink Noise Is All You Need: Colored Noise Exploration in Deep Reinforcement Learning
Linear SCM Identification in the Presence of Confounders and Gaussian Noise
Unearthing Skill-level Insights for Understanding Trade-offs of Foundation Models
GenVP: Generating Visual Puzzles with Contrastive Hierarchical VAEs
Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience
Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks
C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion
LiveBench: A Challenging, Contamination-Limited LLM Benchmark
Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation
Towards GAN Benchmarks Which Require Generalization
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs
SFS: Smarter Code Space Search improves LLM Inference Scaling
The Comparative Power of ReLU Networks and Polynomial Kernels in the Presence of Sparse Latent Structure
Adaptive Instrument Design for Indirect Experiments
TRENDy: Temporal Regression of Effective Nonlinear Dynamics
Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines
PWM: Policy Learning with Multi-Task World Models
Global Optimality Conditions for Deep Neural Networks
Self-Play Preference Optimization for Language Model Alignment
SINGER: Stochastic Network Graph Evolving Operator for High Dimensional PDEs
Generalization in diffusion models arises from geometry-adaptive harmonic representations
Multisize Dataset Condensation
Oryx MLLM: On-Demand Spatial-Temporal Understanding at Arbitrary Resolution
MLLMs Know Where to Look: Training-free Perception of Small Visual Details with Multimodal LLMs
Confidence-Conditioned Value Functions for Offline Reinforcement Learning
Connect, Collapse, Corrupt: Learning Cross-Modal Tasks with Uni-Modal Data
DBA: Distributed Backdoor Attacks against Federated Learning
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions
Accelerating Guided Diffusion Sampling with Splitting Numerical Methods
Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition
Self-Supervised Diffusion Models for Electron-Aware Molecular Representation Learning
Learning Neural Contextual Bandits through Perturbed Rewards
MocoSFL: enabling cross-client collaborative self-supervised learning
MRAG-Bench: Vision-Centric Evaluation for Retrieval-Augmented Multimodal Models
GraphEx: A User-Centric Model-Level Explainer for Graph Neural Networks
FigureQA: An Annotated Figure Dataset for Visual Reasoning
Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness
Don't let your Discriminator be fooled
Designing Concise ConvNets with Columnar Stages
Learning Associative Inference Using Fast Weight Memory
Context-Aware Meta-Learning
BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
Analysis of Video Feature Learning in Two-Stream CNNs on the Example of Zebrafish Swim Bout Classification
Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining
Bridging the Gap between Database Search and De Novo Peptide Sequencing with SearchNovo
Convergence of Distributed Adaptive Optimization with Local Updates
Strategic Classification With Externalities
Robust anomaly detection and backdoor attack detection via differential privacy
Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory
Domain Generalization with MixStyle
GRAIN: Exact Graph Reconstruction from Gradients
SGD with memory: fundamental properties and stochastic acceleration
Unveiling the Pitfalls of Knowledge Editing for Large Language Models
Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains
Improved statistical and computational complexity of the mean-field Langevin dynamics under structured data
Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms
SNODE: Spectral Discretization of Neural ODEs for System Identification
Improving Non-Transferable Representation Learning by Harnessing Content and Style
Learning to Extrapolate: A Transductive Approach
How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
Transformer Meets Boundary Value Inverse Problems
DIVA: Domain Invariant Variational Autoencoder
Natural Language Inference over Interaction Space
A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks
How to 0wn the NAS in Your Spare Time
CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting
Empirical Evaluations of Personalized Federated Learning on Heterogeneous Electronic Health Records
Learning from Rules Generalizing Labeled Exemplars
RecFlow: An Industrial Full Flow Recommendation Dataset
ECD: A Machine Learning Benchmark for Predicting Enhanced-Precision Electronic Charge Density in Crystalline Inorganic Materials
Failures to Find Transferable Image Jailbreaks Between Vision-Language Models
A Learning Based Hypothesis Test for Harmful Covariate Shift
Enhancing End-to-End Autonomous Driving with Latent World Model
CLoSD: Closing the Loop between Simulation and Diffusion for multi-task character control
Object-Aware Inversion and Reassembly for Image Editing
Mapping the Timescale Organization of Neural Language Models
Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting
Constrained Decoding for Cross-lingual Label Projection
Generalization Bounds and Model Complexity for Kolmogorov-Arnold Networks
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning
Expressiveness and Approximation Properties of Graph Neural Networks
Tuning-Free Bilevel Optimization: New Algorithms and Convergence Analysis
LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models
A Watermark for Order-Agnostic Language Models
Matrix Product Sketching via Coordinated Sampling
RaCT: Toward Amortized Ranking-Critical Training For Collaborative Filtering
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach
MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation
Learning From Noisy Singly-labeled Data
The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise
Constrained Bi-Level Optimization: Proximal Lagrangian Value Function Approach and Hessian-free Algorithm
Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Community
MCNC: Manifold-Constrained Reparameterization for Neural Compression
Simple Emergent Action Representations from Multi-Task Policy Training
How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?
Influence-Based Multi-Agent Exploration
Adaptive Self-training Framework for Fine-grained Scene Graph Generation
Randomized Ensembled Double Q-Learning: Learning Fast Without a Model
Feed-forward Propagation in Probabilistic Neural Networks with Categorical and Max Layers
Proactive policing as reinforcement learning
Generalized Convolutional Forest Networks for Domain Generalization and Visual Recognition
Manipulating dropout reveals an optimal balance of efficiency and robustness in biological and machine visual systems
ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks
Symmetric Basis Convolutions for Learning Lagrangian Fluid Mechanics
Robust Model Based Reinforcement Learning Using L1 Adaptive Control
Routing Experts: Learning to Route Dynamic Experts in Existing Multi-modal Large Language Models
NExUME: Adaptive Training and Inference for DNNs under Intermittent Power Environments
No One Representation to Rule Them All: Overlapping Features of Training Methods
Sufficient Context: A New Lens on Retrieval Augmented Generation Systems
Attention, Learn to Solve Routing Problems!
Reliable and Diverse Evaluation of LLM Medical Knowledge Mastery
When will federated learning transfer from generalization to personalization?
Persistent Pre-training Poisoning of LLMs
Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation
A Non-monotonic Self-terminating Language Model
A New Method of Region Embedding for Text Classification
Demystifying Linear MDPs and Novel Dynamics Aggregation Framework
Imitating Graph-Based Planning with Goal-Conditioned Policies
Randomized Automatic Differentiation
Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation
Large Language Models Are Not Robust Multiple Choice Selectors
Clustered Federated Learning with Slightly Skewed Labels
Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis
Time Fairness in Online Knapsack Problems
Self-supervised learning with rotation-invariant kernels
The Optimization Landscape of SGD Across the Feature Learning Strength
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Universal approximation power of deep residual neural networks via nonlinear control theory
LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence
Compositional Entailment Learning for Hyperbolic Vision-Language Models
S2AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic
Learning a Generative Model for Validity in Complex Discrete Structures
Poly-View Contrastive Learning
FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing
Transfer Learning with Deep Tabular Models
Progressive3D: Progressively Local Editing for Text-to-3D Content Creation with Complex Semantic Prompts
Don't Settle for Average, Go for the Max: Fuzzy Sets and Max-Pooled Word Vectors
Linearly Mapping from Image to Text Space
Robust Active Distillation
Overcoming False Illusions in Real-World Face Restoration with Multi-Modal Guided Diffusion Model
Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime
Predicting Embryo Morphokinetics in Videos with Late Fusion Nets & Dynamic Decoders
DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity
Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization
M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering
Path Integral Sampler: A Stochastic Control Approach For Sampling
Adversarial Retriever-Ranker for Dense Text Retrieval
SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation
Hierarchical Reinforcement Learning via Advantage-Weighted Information Maximization
Conservative Contextual Bandits: Beyond Linear Representations
Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints
Encoding and Decoding Representations with Sum- and Max-Product Networks
CLIP-ViP: Adapting Pre-trained Image-Text Model to Video-Language Alignment
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression
APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding
Neural Thompson Sampling
Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design
Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents
Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization
Data Scaling Laws in Imitation Learning for Robotic Manipulation
Instance-wise Batch Label Restoration via Gradients in Federated Learning
An Emulator for Fine-tuning Large Language Models using Small Language Models
Hyperbolic Deep Reinforcement Learning for Continuous Control
Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts
Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning
Are Models Biased on Text without Gender-related Language?
Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
Both Ears Wide Open: Towards Language-Driven Spatial Audio Generation
LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers
Mask-Based Modeling for Neural Radiance Fields
Adversarial Causal Bayesian Optimization
Compressing LLMs: The Truth is Rarely Pure and Never Simple
Projective Proximal Gradient Descent for Nonconvex Nonsmooth Optimization: Fast Convergence Without Kurdyka-Lojasiewicz (KL) Property
Neural Spatio-Temporal Point Processes
FairDen: Fair Density-Based Clustering
Cached Multi-Lora Composition for Multi-Concept Image Generation
Specformer: Spectral Graph Neural Networks Meet Transformers
Global Explainability of GNNs via Logic Combination of Learned Concepts
Few-Shot Bayesian Optimization with Deep Kernel Surrogates
Feature Importance Analysis for Mini Mental Status Score Prediction in Alzheimer's Disease
Learning to Solve Differential Equation Constrained Optimization Problems
HexaConv
Multi-timescale Representation Learning in LSTM Language Models
Differentiable Expectation-Maximization for Set Representation Learning
TSC-Net: Prediction of Pedestrian Trajectories by Trajectory-Scene-Cell Classification
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning
SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
Synthesizing Realistic fMRI: A Physiological Dynamics-Driven Hierarchical Diffusion Model for Efficient fMRI Acquisition
Continual Normalization: Rethinking Batch Normalization for Online Continual Learning
Lite Transformer with Long-Short Range Attention
Generalized Consistency Trajectory Models for Image Manipulation
DORSal: Diffusion for Object-centric Representations of Scenes et al
TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks
Are Human-generated Demonstrations Necessary for In-context Learning?
SparsyFed: Sparse Adaptive Federated Learning
FaceShot: Bring Any Character into Life
Sparse Token Transformer with Attention Back Tracking
Episodic Exploration for Deep Deterministic Policies for StarCraft Micromanagement
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction
Stochastic Activation Pruning for Robust Adversarial Defense
Multi-objective antibody design with constrained preference optimization
Are Efficient Deep Representations Learnable?
Generating Counterfactual Explanations Using Cardinality Constraints
A Benchmark Study on Calibration
Model compression via distillation and quantization
Trajectory-Class-Aware Multi-Agent Reinforcement Learning
Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
pGS-CAM: Interpretable LiDAR Point Cloud Semantic Segmentation via Gradient Based Localization
The Role of Momentum Parameters in the Optimal Convergence of Adaptive Polyak's Heavy-ball Methods
Meta-Learning for Subject Adaptation in Low-Data Environments for EEG-Based Motor Imagery Brain-Computer Interfaces
NeuPL: Neural Population Learning
EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model
Towards Mixed-initiative generation of multi-channel sequential structure
Value Propagation Networks
Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow
InterMask: 3D Human Interaction Generation via Collaborative Masked Modeling
EVA: Geometric Inverse Design for Fast Protein Motif-Scaffolding with Coupled Flow
ReGenesis: LLMs can Grow into Reasoning Generalists via Self-Improvement
Value-aligned Behavior Cloning for Offline Reinforcement Learning via Bi-level Optimization
Memory Matching Networks for Genomic Sequence Classification
Coherence-based Label Propagation over Time Series for Accelerated Active Learning
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes
Common Sense Initialization of Mixture Density Networks for Motion Planning with Overestimated Number of Components
Bayesian Coreset Optimization for Personalized Federated Learning
Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response
Structure by Architecture: Structured Representations without Regularization
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics
COMBO: Compositional World Models for Embodied Multi-Agent Cooperation
Layout-your-3D: Controllable and Precise 3D Generation with 2D Blueprint
Learning a Meta-Solver for Syntax-Guided Program Synthesis
Efficient Dictionary Learning with Switch Sparse Autoencoders
Generating Multi-Agent Trajectories using Programmatic Weak Supervision
Learning Value Functions from Undirected State-only Experience
Adversarial Attacks on Fairness of Graph Neural Networks
Beware of Calibration Data for Pruning Large Language Models
Generalized Video Moment Retrieval
Rethinking Multiple-Instance Learning From Feature Space to Probability Space
Augmenting Transformers with Recursively Composed Multi-grained Representations
Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth
Easy Differentially Private Linear Regression
Towards Image Understanding from Deep Compression Without Decoding
Adversarial Unlearning of Backdoors via Implicit Hypergradient
DOPL: Direct Online Preference Learning for Restless Bandits with Preference Feedback
iFlood: A Stable and Effective Regularizer
Eidetic 3D LSTM: A Model for Video Prediction and Beyond
Is Watermarking LLM-Generated Code Robust?
Federated Q-Learning: Linear Regret Speedup with Low Communication Cost
Flat Reward in Policy Parameter Space Implies Robust Reinforcement Learning
DOCS: Quantifying Weight Similarity for Deeper Insights into Large Language Models
Buy 4 REINFORCE Samples, Get a Baseline for Free!
Correcting experience replay for multi-agent communication
SymDiff: Equivariant Diffusion via Stochastic Symmetrisation
IDInit: A Universal and Stable Initialization Method for Neural Network Training
Text Generation by Learning from Demonstrations
Semi-parametric topological memory for navigation
SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models
MrSteve: Instruction-Following Agents in Minecraft with What-Where-When Memory
Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing
ThunderKittens: Simple, Fast, and Adorable Kernels
Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets
BOND: Aligning LLMs with Best-of-N Distillation
Efficient Entropy For Policy Gradient with Multi-Dimensional Action Space
Improving Adversarial Robustness via Channel-wise Activation Suppressing
ViewCo: Discovering Text-Supervised Segmentation Masks via Multi-View Semantic Consistency
Protein-ligand binding representation learning from fine-grained interactions
MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
Hybrid Random Features
SAFENet: A Secure, Accurate and Fast Neural Network Inference
Large Language Models for Wearable Data Analysis and Interpretation
Reparameterization through Spatial Gradient Scaling
Image and Video Tokenization with Binary Spherical Quantization
Basic Binary Convolution Unit for Binarized Image Restoration Network
ES-MAML: Simple Hessian-Free Meta Learning
Leave-one-out Distinguishability in Machine Learning
Systematic Rectification of Language Models via Dead-end Analysis
Learning Language Representations with Logical Inductive Bias
On the Parameterization of Second-Order Optimization Effective towards the Infinite Width
CATER: A diagnostic dataset for Compositional Actions & TEmporal Reasoning
Moner: Motion Correction in Undersampled Radial MRI with Unsupervised Neural Representation
Can gradient clipping mitigate label noise?
Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values
Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold
Learning in reverse causal strategic environments with ramifications on two sided markets
Spherical CNNs on Unstructured Grids
Efficient Causal Decision Making with One-sided Feedback
Safety Layers in Aligned Large Language Models: The Key to LLM Security
Fréchet Wavelet Distance: A Domain-Agnostic Metric for Image Generation
Layer-wise linear mode connectivity
Decision Transformer under Random Frame Dropping
On Trajectory Augmentations for Off-Policy Evaluation
GameArena: Evaluating LLM Reasoning through Live Computer Games
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series
Ultra-Sparse Memory Network
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization
Sparse tree-based Initialization for Neural Networks
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning
Divergence-enhanced Knowledge-guided Context Optimization for Visual-Language Prompt Tuning