yusuke1997/dblp-id-title huggingface dataset:
Reinforcement Learning Algorithm Selection
Breaking Correlation Shift via Conditional Invariant Regularizer
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies
Adversarial Lipschitz Regularization
BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning
Towards Faithful XAI Evaluation via Generalization-Limited Backdoor Watermark
Spurious Feature Diversification Improves Out-of-distribution Generalization
ArchLock: Locking DNN Transferability at the Architecture Level with a Zero-Cost Binary Predictor
ToM2C: Target-oriented Multi-agent Communication and Cooperation with Theory of Mind
Combinatorial CNNs for words
Fair Classifiers that Abstain without Harm
kNN Attention Demystified: A Theoretical Exploration for Scalable Transformers
Evaluating Disentanglement of Structured Representations
Asymptotics of Wide Networks from Feynman Diagrams
Data-Efficient Reinforcement Learning with Self-Predictive Representations
Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder
Transfer Learning for Sequences via Learning to Collocate
Scalable Estimation via LSH Samplers (LSS)
Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations
Network Insensitivity to Parameter Noise via Parameter Attack During Training
SVBench: A Benchmark with Temporal Multi-Turn Dialogues for Streaming Video Understanding
Empowering Users in Digital Privacy Management through Interactive LLM-Based Agents
Learning Personalized Causally Invariant Representations for Heterogeneous Federated Clients
AnyTouch: Learning Unified Static-Dynamic Representation across Multiple Visuo-tactile Sensors
Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs
Explaining Modern Gated-Linear RNNs via a Unified Implicit Attention Formulation
Cross-Layer Retrospective Retrieving via Layer Attention
On the Identification of Temporal Causal Representation with Instantaneous Dependence
Reverse Diffusion Monte Carlo
Privacy Amplification for Matrix Mechanisms
Globally Optimal Training of Neural Networks with Threshold Activation Functions
Adaptive Window Pruning for Efficient Local Motion Deblurring
The Implicit Bias of Gradient Descent on Separable Data
Real-time design of architectural structures with differentiable mechanics and neural networks
Contextual Image Masking Modeling via Synergized Contrasting without View Augmentation for Faster and Better Visual Pretraining
Empirical or Invariant Risk Minimization? A Sample Complexity Perspective
SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
Regression with Label Differential Privacy
Neural Causal Models for Counterfactual Identification and Estimation
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs
Discretization-invariance? On the Discretization Mismatch Errors in Neural Operators
SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations
A Differentially Private Clustering Algorithm for Well-Clustered Graphs
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
IDA-VLM: Towards Movie Understanding via ID-Aware Large Vision-Language Model
SMI-Editor: Edit-based SMILES Language Model with Fragment-level Supervision
Measuring axiomatic soundness of counterfactual image models
Cross Domain Vulnerability Detection using Graph Contrastive Learning
Large Batch Simulation for Deep Reinforcement Learning
Deep Networks and the Multiple Manifold Problem
Differentially Private Fine-tuning of Language Models
A Percolation Model of Emergence: Analyzing Transformers Trained on a Formal Language
Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations
Differentially private learners for heterogeneous treatment effects
Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling
Dealing with Non-Stationarity in MARL via Trust-Region Decomposition
Diet Networks: Thin Parameters for Fat Genomics
Learnable Behavior Control: Breaking Atari Human World Records via Sample-Efficient Behavior Selection
LLaRA: Supercharging Robot Learning Data for Vision-Language Policy
Learning a SAT Solver from Single-Bit Supervision
Network Deconvolution
Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence
Parameter-Efficient Fine-Tuning Design Spaces
Spatio-Temporal Graph Scattering Transform
SIMPLE: Specialized Model-Sample Matching for Domain Generalization
MAP: Multi-Human-Value Alignment Palette
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs
Combinatorial Pure Exploration of Causal Bandits
On the Effect of Batch Size in Byzantine-Robust Distributed Learning
Equivariant Masked Position Prediction for Efficient Molecular Representation
Neural Program Lattices
CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repair
A Dynamical View of the Question of Why
SMART: Self-supervised Multi-task pretrAining with contRol Transformers
A Mixture-of-Expert Approach to RL-based Dialogue Management
Learning to Plan Before Answering: Self-Teaching LLMs to Learn Abstract Plans for Problem Solving
AdaManip: Adaptive Articulated Object Manipulation Environments and Policy Learning
Do Deep Neural Network Solutions Form a Star Domain?
Prediction Risk and Estimation Risk of the Ridgeless Least Squares Estimator under General Assumptions on Regression Errors
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity
Generate rather than Retrieve: Large Language Models are Strong Context Generators
Steering Large Language Models between Code Execution and Textual Reasoning
Sigma Delta Quantized Networks
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning
Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning
Network Inversion of Binarised Neural Nets
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks
Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control
Improving VAEs' Robustness to Adversarial Attack
Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance
When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach
The Power of Regularization in Solving Extensive-Form Games
xFinder: Large Language Models as Automated Evaluators for Reliable Evaluation
Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning
Fully differentiable full-atom protein backbone generation
Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation
Relay Diffusion: Unifying diffusion process across resolutions for image synthesis
Hierarchical Representations for Efficient Architecture Search
Incorporating long-range consistency in CNN-based texture generation
COFlowNet: Conservative Constraints on Flows Enable High-Quality Candidate Generation
On the Certified Robustness for Ensemble Models and Beyond
Learning in temporally structured environments
Better Instruction-Following Through Minimum Bayes Risk
UniCon: Unidirectional Information Flow for Effective Control of Large-Scale Diffusion Models
Modeling the Long Term Future in Model-Based Reinforcement Learning
Private Image Reconstruction from System Side Channels Using Generative Models
Batched Low-Rank Adaptation of Foundation Models
CR2PQ: Continuous Relative Rotary Positional Query for Dense Visual Representation Learning
Net-DNF: Effective Deep Modeling of Tabular Data
Action Semantics Network: Considering the Effects of Actions in Multiagent Systems
Unposed Sparse Views Room Layout Reconstruction in the Age of Pretrain Model
Doubly Optimal Policy Evaluation for Reinforcement Learning
Charged Point Normalization: An Efficient Solution to the Saddle Point Problem
The Marginal Value of Momentum for Small Learning Rate SGD
Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit
Thalamus: a brain-inspired algorithm for biologically-plausible continual learning and disentangled representations
Perception Updating Networks: On architectural constraints for interpretable video generative models
A Spark of Vision-Language Intelligence: 2-Dimensional Autoregressive Transformer for Efficient Finegrained Image Generation
On the Relationship between Self-Attention and Convolutional Layers
Semantically Decomposing the Latent Spaces of Generative Adversarial Networks
Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation
On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
Learning to Generalize across Domains on Single Test Samples
GraphPulse: Topological representations for temporal graph property prediction
Tranquil Clouds: Neural Networks for Learning Temporally Coherent Features in Point Clouds
Debiasing Attention Mechanism in Transformer without Demographics
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula
HyperPLR: Hypergraph Generation through Projection, Learning, and Reconstruction
MixEval-X: Any-to-any Evaluations from Real-world Data Mixture
Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning
PINTO: Faithful Language Reasoning Using Prompt-Generated Rationales
A Language and Compiler View on Differentiable Programming
Policy-Based Self-Competition for Planning Problems
Actor-Critic Policy Optimization in a Large-Scale Imperfect-Information Game
Learning Latent Representations in Neural Networks for Clustering through Pseudo Supervision and Graph-based Activity Regularization
Prototypical Calibration for Few-shot Learning of Language Models
HyperFace: Generating Synthetic Face Recognition Datasets by Exploring Face Embedding Hypersphere
Efficient Action-Constrained Reinforcement Learning via Acceptance-Rejection Method and Augmented MDPs
Information asymmetry in KL-regularized RL
Contextual Self-paced Learning for Weakly Supervised Spatio-Temporal Video Grounding
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication
The Computational Complexity of Circuit Discovery for Inner Interpretability
Fiber Monte Carlo
Decompose to Generalize: Species-Generalized Animal Pose Estimation
Pooling Image Datasets with Multiple Covariate Shift and Imbalance
Data Taggants: Dataset Ownership Verification Via Harmless Targeted Data Poisoning
Boosting Causal Discovery via Adaptive Sample Reweighting
SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning
Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks
Provable Defense Against Geometric Transformations
Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs
On Robustness of Neural Ordinary Differential Equations
Modeling Uncertainty with Hedged Instance Embeddings
Manifold Induced Biases for Zero-shot and Few-shot Detection of Generated Images
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization
Quantifying the Cost of Reliable Photo Authentication via High-Performance Learned Lossy Representations
Online Adversarial Purification based on Self-supervised Learning
Group equivariant neural posterior estimation
Representation Learning for Low-rank General-sum Markov Games
Automated Proof Generation for Rust Code via Self-Evolution
Thin-Shell Object Manipulations With Differentiable Physics Simulations
Towards Transparent Time Series Forecasting
Quantum-PEFT: Ultra parameter-efficient fine-tuning
On Minimizing Adversarial Counterfactual Error in Adversarial Reinforcement Learning
Ask Me Anything: A simple strategy for prompting language models
Reverse Engineering of Imperceptible Adversarial Image Perturbations
Simplicial Representation Learning with Neural k-Forms
Generative Code Modeling with Graphs
Structured Neural Summarization
SD-NAE: Generating Natural Adversarial Examples with Stable Diffusion
MetaMorph: Learning Universal Controllers with Transformers
SMT: Fine-Tuning Large Language Models with Sparse Matrices
High Probability Generalization Bounds with Fast Rates for Minimax Problems
EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents
SynQ: Accurate Zero-shot Quantization by Synthesis-aware Fine-tuning
Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation
Alternating Multi-bit Quantization for Recurrent Neural Networks
Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass
DiffPC: Diffusion-based High Perceptual Fidelity Image Compression with Semantic Refinement
On the Sensitivity of Reward Inference to Misspecified Human Models
End-to-End Egospheric Spatial Memory
Fooling Explanations in Text Classifiers
Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process
Model-Based Visual Planning with Self-Supervised Functional Distances
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
Raidar: geneRative AI Detection viA Rewriting
Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top
Towards Category Unification of 3D Single Object Tracking on Point Clouds
BANGS: Game-theoretic Node Selection for Graph Self-Training
SmartPlay : A Benchmark for LLMs as Intelligent Agents
Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization
CrossMatch: Cross-Classifier Consistency Regularization for Open-Set Single Domain Generalization
Bounds on Over-Parameterization for Guaranteed Existence of Descent Paths in Shallow ReLU Networks
FILM: Following Instructions in Language with Modular Methods
Toward effective protection against diffusion-based mimicry through score distillation
LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization
Towards the Limit of Network Quantization
Trained Ternary Quantization
Polynomial Width is Sufficient for Set Representation with High-dimensional Features
Transformer Encoder Satisfiability: Complexity and Impact on Formal Reasoning
Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model
Boosting the Cycle Counting Power of Graph Neural Networks with I$^2$-GNNs
Fantastic Generalization Measures are Nowhere to be Found
Compositionality with Variation Reliably Emerges in Neural Networks
Generating Graphs via Spectral Diffusion
The Gambler's Problem and Beyond
Imbedding Deep Neural Networks
FIT: A Metric for Model Sensitivity
Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network
Safety Alignment Should be Made More Than Just a Few Tokens Deep
Re-Imagining Multimodal Instruction Tuning: A Representation View
An Equal-Size Hard EM Algorithm for Diverse Dialogue Generation
FigGen: Text to Scientific Figure Generation
Deep Reinforcement Learning for Modelling Protein Complexes
Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning
Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks
Space-Time Graph Neural Networks
One Student Knows All Experts Know: From Sparse to Dense
DAM: Towards a Foundation Model for Forecasting
Neural Architecture Retrieval
STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables
Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks
Trainability Preserving Neural Pruning
SetCSE: Set Operations using Contrastive Learning of Sentence Embeddings
InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior
NetMoE: Accelerating MoE Training through Dynamic Sample Placement
A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data
SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data
Exploring extreme parameter compression for pre-trained language models
AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorials
A Mutual Information Perspective on Federated Contrastive Learning
Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning
BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity
Graph Constrained Reinforcement Learning for Natural Language Action Spaces
Proteina: Scaling Flow-based Protein Structure Generative Models
Closing the Curious Case of Neural Text Degeneration
Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search
SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image And Video Generation
Habitat 3.0: A Co-Habitat for Humans, Avatars, and Robots
Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-tuning
Generalized Behavior Learning from Diverse Demonstrations
ACC-Collab: An Actor-Critic Approach to Multi-Agent LLM Collaboration
Self-Supervised Geometric Correspondence for Category-Level 6D Object Pose Estimation in the Wild
Blurring Diffusion Models
Gaussian Splatting Lucas-Kanade
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
MoVie: Revisiting Modulated Convolutions for Visual Counting and Beyond
The geometry of integration in text classification RNNs
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition
DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures
High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize
Open Question Answering over Tables and Text
Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion
The Same but Different: Structural Similarities and Differences in Multilingual Language Modeling
Mind the Pad - CNNs Can Develop Blind Spots
Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity
CrossVoice: Crosslingual Prosody Preserving Cascade-S2ST using Transfer Learning
Even a single simple augmentation with Self-Supervised Learning can be helpful for the downstream tasks
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
Learned Learning Rate Schedules for Deep Neural Network Training Using Reinforcement Learning
Can a MISL Fly? Analysis and Ingredients for Mutual Information Skill Learning
Equivariant Transformers for Neural Network based Molecular Potentials
AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ
Towards the first adversarially robust neural network model on MNIST
What Makes Convolutional Models Great on Long Sequence Modeling?
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
SmartFRZ: An Efficient Training Framework using Attention-Based Layer Freezing
Two-stage LLM Fine-tuning with Less Specialization and More Generalization
Cold fusion: Training Seq2seq Models Together with Language Models
Robust And Interpretable Blind Image Denoising Via Bias-Free Convolutional Neural Networks
Taming GANs with Lookahead-Minmax
Explanation by Progressive Exaggeration
Learning to Solve Bilevel Programs with Binary Tender
Grounding Graph Network Simulators using Physical Sensor Observations
NL-Eye: Abductive NLI For Images
Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex
Consistency Models as a Rich and Efficient Policy Class for Reinforcement Learning
On the geometry of generalization and memorization in deep neural networks
Language Model Self-improvement by Reinforcement Learning Contemplation
Looped Transformers are Better at Learning Learning Algorithms
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks
Sharper Bounds for Uniformly Stable Algorithms with Stationary Mixing Process
Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance
Clifford Group Equivariant Simplicial Message Passing Networks
Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning
NetFormer: An interpretable model for recovering dynamical connectivity in neuronal population dynamics
Motion Control of High-Dimensional Musculoskeletal Systems with Hierarchical Model-Based Planning
Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures
Autocorrelation Matters: Understanding the Role of Initialization Schemes for State Space Models
Neural Lagrangian Schrödinger Bridge: Diffusion Modeling for Population Dynamics
VoxDialogue: Can Spoken Dialogue Systems Understand Information Beyond Words?
Tensor Decompositions for Temporal Knowledge Base Completion
On the Vulnerability of Adversarially Trained Models Against Two-faced Attacks
Synchromesh: Reliable Code Generation from Pre-trained Language Models
Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations
Neural Interactive Proofs
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
Learning to Annotate Part Segmentation with Gradient Matching
High-Capacity Expert Binary Networks
Rarity Score : A New Metric to Evaluate the Uncommonness of Synthesized Images
Residual-MPPI: Online Policy Customization for Continuous Control
Trajectory-LLM: A Language-based Data Generator for Trajectory Prediction in Autonomous Driving
ThinK: Thinner Key Cache by Query-Driven Pruning
A Closer Look at Deep Policy Gradients
Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs
Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline
Masked Autoencoders with Multi-Window Local-Global Attention Are Better Audio Learners
Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity
Consistent algorithms for multi-label classification with macro-at-k metrics
Understanding Composition of Word Embeddings via Tensor Decomposition
Large-Scale Representation Learning on Graphs via Bootstrapping
Retrieval Augmented Diffusion Model for Structure-informed Antibody Design and Optimization
Improving Intrinsic Exploration by Creating Stationary Objectives
Diffusion Model for Dense Matching
Fast Differentiable Matrix Square Root
What Matters to You? Towards Visual Representation Alignment for Robot Learning
Concept Bottleneck Language Models For Protein Design
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks
Learning to Schedule Learning rate with Graph Neural Networks
Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation
Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks
Variational Network Quantization
Sample then Identify: A General Framework for Risk Control and Assessment in Multimodal Large Language Models
Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks
ProxQuant: Quantized Neural Networks via Proximal Operators
Improving Long-Text Alignment for Text-to-Image Diffusion Models
Unleashing the Potential of Vision-Language Pre-Training for 3D Zero-Shot Lesion Segmentation via Mask-Attribute Alignment
GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting
SeCom: On Memory Construction and Retrieval for Personalized Conversational Agents
Improving the Improved Training of Wasserstein GANs: A Consistency Term and Its Dual Effect
Linear combinations of latents in generative models: subspaces and beyond
Evaluating Language Model Agency Through Negotiations
XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning
Averaging Rate Scheduler for Decentralized Learning on Heterogeneous Data
Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement
Uni2Det: Unified and Universal Framework for Prompt-Guided Multi-dataset 3D Detection
Tight Lower Bounds under Asymmetric High-Order Hölder Smoothness and Uniform Convexity