yusuke1997/dblp-id-title huggingface dataset:
Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning
A First-Occupancy Representation for Reinforcement Learning
Real-Fake: Effective Training Data Synthesis Through Distribution Matching
Direct Post-Training Preference Alignment for Multi-Agent Motion Generation Model Using Implicit Feedback from Pre-training Demonstrations
Biologically Constrained Barrel Cortex Model Integrates Whisker Inputs and Replicates Key Brain Network Dynamics
TDDBench: A Benchmark for Training data detection
Block-Attention for Efficient Prefilling
Neural Symbolic Reader: Scalable Integration of Distributed and Symbolic Representations for Reading Comprehension
Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training
Language Imbalance Driven Rewarding for Multilingual Self-improving
End-to-End Learning of Probabilistic Hierarchies on Graphs
Reinforcement Symbolic Regression Machine
Learning to Estimate Single-View Volumetric Flow Motions without 3D Supervision
Sample-Efficient Multi-Agent RL: An Optimization Perspective
Overfitting for Fun and Profit: Instance-Adaptive Data Compression
Are Bert Family Good Instruction Followers? A Study on Their Potential And Limitations
Query-efficient Meta Attack to Deep Neural Networks
Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning
RetroBridge: Modeling Retrosynthesis with Markov Bridges
A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond
Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought
Can We Ignore Labels in Out of Distribution Detection?
LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation
PAC-Bayes Information Bottleneck
How Does SimSiam Avoid Collapse Without Negative Samples? A Unified Understanding with Self-supervised Contrastive Learning
SlotFormer: Unsupervised Visual Dynamics Simulation with Object-Centric Models
Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL
Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns
SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition
DBQ-SSD: Dynamic Ball Query for Efficient 3D Object Detection
D4AM: A General Denoising Framework for Downstream Acoustic Models
Generative Language-Grounded Policy in Vision-and-Language Navigation with Bayes' Rule
ProtPainter: Draw or Drag Protein via Topology-guided Diffusion
Function-Consistent Feature Distillation
Transfer Learning for Global Feature Importance Measurements
MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models
Emo: Earth Mover Distance Optimization for Auto-Regressive Language Modeling
Generalizable Human Gaussians from Single-View Image
PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods
Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting
Metalic: Meta-Learning In-Context with Protein Language Models
Revealing and Reducing Gender Biases in Vision and Language Assistants (VLAs)
Private Zeroth-Order Nonsmooth Nonconvex Optimization
The asymptotic spectrum of the Hessian of DNN throughout training
ToVE: Efficient Vision-Language Learning via Knowledge Transfer from Vision Experts
Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, And No Retraining
Colorful Cutout: Enhancing Image Data Augmentation with Curriculum Learning
SUMNAS: Supernet with Unbiased Meta-Features for Neural Architecture Search
Predicting Emergent Abilities with Infinite Resolution Evaluation
Additive Margin Softmax for Face Verification
A Learning Theoretic Perspective on Local Explainability
When to Make and Break Commitments?
Interactive Speculative Planning: Enhance Agent Efficiency through Co-design of System and User Interface
On Robust Concepts and Small Neural Nets
Stylized Offline Reinforcement Learning: Extracting Diverse High-Quality Behaviors from Heterogeneous Datasets
Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization
Foundation Models Secretly Understand Neural Network Weights: Enhancing Hypernetwork Architectures with Foundation Models
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models
Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models
Large Scale Optimal Transport and Mapping Estimation
Improving MMD-GAN Training with Repulsive Loss Function
Shapley explainability on the data manifold
NeRN: Learning Neural Representations for Neural Networks
Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps
Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation
Bayesian Framework for Gradient Leakage
Gradient-based Optimization of Neural Network Architecture
Visually Guided Decoding: Gradient-Free Hard Prompt Inversion with Language Models
A Smooth Optimisation Perspective on Training Feedforward Neural Networks
Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery
Selective Label Enhancement Learning for Test-Time Adaptation
Mask-DPO: Generalizable Fine-grained Factuality Alignment of LLMs
Token Statistics Transformer: Linear-Time Attention via Variational Rate Reduction
MDSGen: Fast and Efficient Masked Diffusion Temporal-Aware Transformers for Open-Domain Sound Generation
Cross-Modal Safety Mechanism Transfer in Large Vision-Language Models
Unrolling PALM for Sparse Semi-Blind Source Separation
Learning to Generate Samples from Noise through Infusion Training
As Simple as Fine-tuning: LLM Alignment via Bidirectional Negative Feedback Loss
Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
Progressive Learning and Disentanglement of Hierarchical Representations
Koopman Neural Operator Forecaster for Time-series with Temporal Distributional Shifts
Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency
Learning 3D Particle-based Simulators from RGB-D Videos
AgentStudio: A Toolkit for Building General Virtual Agents
Detecting Extrapolation with Local Ensembles
Sliced Kernelized Stein Discrepancy
Identifying through Flows for Recovering Latent Representations
Training deep neural-networks using a noise adaptation layer
HALL-E: Hierarchical Neural Codec Language Model for Minute-Long Zero-Shot Text-to-Speech Synthesis
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Tamper-Resistant Safeguards for Open-Weight LLMs
Privately Aligning Language Models with Reinforcement Learning
SynCamMaster: Synchronizing Multi-Camera Video Generation from Diverse Viewpoints
Learnability of convolutional neural networks for infinite dimensional input via mixed and anisotropic smoothness
Look, Remember and Reason: Grounded Reasoning in Videos with Language Models
SiReRAG: Indexing Similar and Related Information for Multihop Reasoning
Masked Audio Generation using a Single Non-Autoregressive Transformer
Lsh-Sampling breaks the Computational chicken-and-egg Loop in adaptive stochastic Gradient estimation
Label Propagation with Weak Supervision
Seer: Language Instructed Video Prediction with Latent Diffusion Models
Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning
HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning
Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment
Spatially-Aware Transformers for Embodied Agents
Learning From Simplicial Data Based on Random Walks and 1D Convolutions
Toward Adversarial Training on Contextualized Language Representation
Learning Soft Constraints From Constrained Expert Demonstrations
Local SGD Converges Fast and Communicates Little
Learning to Defense by Learning to Attack
Clifford Neural Layers for PDE Modeling
Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
Can LLMs Solve Longer Math Word Problems Better?
Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation
Modeling dynamic social vision highlights gaps between deep learning and humans
LeanAgent: Lifelong Learning for Formal Theorem Proving
∞-Diff: Infinite Resolution Diffusion with Subsampled Mollified States
Exponential Topology-enabled Scalable Communication in Multi-agent Reinforcement Learning
Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games
Multi-Label Test-Time Adaptation with Bound Entropy Minimization
f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization
Learning Causal Models from Conditional Moment Restrictions by Importance Weighting
Can recurrent neural networks warp time?
Generation and Comprehension Hand-in-Hand: Vision-guided Expression Diffusion for Boosting Referring Expression Generation and Comprehension
LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied Agents
Efficient Multi-agent Reinforcement Learning by Planning
Algorithms for Caching and MTS with reduced number of predictions
An Auditing Test to Detect Behavioral Shift in Language Models
On the relationship between Normalising Flows and Variational- and Denoising Autoencoders
Episodic Memories Generation and Evaluation Benchmark for Large Language Models
CAKE: Cascading and Adaptive KV Cache Eviction with Layer Preferences
Towards image compression with perfect realism at ultra-low bitrates
Label-Efficient Semantic Segmentation with Diffusion Models
Stabilizing Adversarial Nets with Prediction Methods
Model Merging by Uncertainty-Based Gradient Matching
Cyclic Contrastive Knowledge Transfer for Open-Vocabulary Object Detection
Context-enriched molecule representations improve few-shot drug discovery
Label-Focused Inductive Bias over Latent Object Features in Visual Classification
Scalable Benchmarking and Robust Learning for Noise-Free Ego-Motion and 3D Reconstruction from Noisy Video
Deep Neural Networks Tend To Extrapolate Predictably
Prompt Engineering and Calibration for Zero-Shot Commonsense Reasoning
Towards Understanding Regularization in Batch Normalization
Can an Image Classifier Suffice For Action Recognition?
Language model compression with weighted low-rank factorization
Adversarial Feature Map Pruning for Backdoor
Unsupervised Perceptual Rewards for Imitation Learning
MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework
Intent3D: 3D Object Detection in RGB-D Scans Based on Human Intention
LEMON: Lossless model expansion
Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks
COPER: Correlation-based Permutations for Multi-View Clustering
Rethinking Artistic Copyright Infringements In the Era Of Text-to-Image Generative Models
Gradients explode - Deep Networks are shallow - ResNet explained
Gradient Descent Provably Optimizes Over-parameterized Neural Networks
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study
Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks
Do LLMs have Consistent Values?
Replicable Bandits
Large Scale Knowledge Washing
Step-by-Step Reasoning for Math Problems via Twisted Sequential Monte Carlo
Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling
Sparse Quantized Spectral Clustering
Learning to Move with Affordance Maps
Representation learning for improved interpretability and classification accuracy of clinical factors from EEG
Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks
A framework for benchmarking Class-out-of-distribution detection and its application to ImageNet
Probabilistic Adaptation of Black-Box Text-to-Video Models
AI2TALE: An Innovative Information Theory-based Approach for Learning to Localize Phishing Attacks
Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation
Neural Agents Struggle to Take Turns in Bidirectional Emergent Communication
DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs
STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning
TIGER: Time-frequency Interleaved Gain Extraction and Reconstruction for Efficient Speech Separation
A Theoretical Perspective: How to Prevent Model Collapse in Self-consuming Training Loops
Grounded Object-Centric Learning
AdaRankGrad: Adaptive Gradient Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning
Learning Hierarchical Polynomials with Three-Layer Neural Networks
Pseudo-Generalized Dynamic View Synthesis from a Video
Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods
Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP
Protein Sequence and Structure Co-Design with Equivariant Translation
The Power of LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions
UNICORN: A Unified Backdoor Trigger Inversion Framework
CarbonSense: A Multimodal Dataset and Baseline for Carbon Flux Modelling
DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation
SAVA: Scalable Learning-Agnostic Data Valuation
Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech
Decoupling Layout from Glyph in Online Chinese Handwriting Generation
Partial Rankings of Optimizers
Continuous Invariance Learning
Weaker MVI Condition: Extragradient Methods with Multi-Step Exploration
Connecting the Dots Between MLE and RL for Sequence Generation
Learning Efficient Online 3D Bin Packing on Packing Configuration Trees
Timer-XL: Long-Context Transformers for Unified Time Series Forecasting
Rethinking Compression: Reduced order modelling of Latent Features in Large Language Models
IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models
Imitation Learning from Visual Data with Multiple Intentions
ADAPT: Attentive Self-Distillation and Dual-Decoder Prediction Fusion for Continual Panoptic Segmentation
KoLA: Carefully Benchmarking World Knowledge of Large Language Models
PIG: Physics-Informed Gaussians as Adaptive Parametric Mesh Representations
A Signal Propagation Perspective for Pruning Neural Networks at Initialization
Hindsight Foresight Relabeling for Meta-Reinforcement Learning
PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis
Mixture of LoRA Experts
Revisiting Mode Connectivity in Neural Networks with Bezier Surface
Satisficing Regret Minimization in Bandits
A Simple Framework for Open-Vocabulary Zero-Shot Segmentation
Continuous-Multiple Image Outpainting in One-Step via Positional Query and A Diffusion-based Approach
Federated Neural Bandits
NovelQA: Benchmarking Question Answering on Documents Exceeding 200K Tokens
Learning Discrete Weights Using the Local Reparameterization Trick
Bayes Conditional Distribution Estimation for Knowledge Distillation Based on Conditional Mutual Information
Successor Heads: Recurring, Interpretable Attention Heads In The Wild
End-to-End Learnable Masks With Differentiable Indexing
Oblique Decision Trees from Derivatives of ReLU Networks
Calibrating the Rigged Lottery: Making All Tickets Reliable
Beyond Surface Structure: A Causal Assessment of LLMs' Comprehension ability
Ready-to-React: Online Reaction Policy for Two-Character Interaction Generation
Insights into the mechanism behind reusing Teacher's classifier in Knowledge Distillation
Learning-Augmented Data Stream Algorithms
Data Selection via Optimal Control for Language Models
Sliced Cramer Synaptic Consolidation for Preserving Deeply Learned Representations
Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs
Differentiable and Learnable Wireless Simulation with Geometric Transformers
Graph-Guided Scene Reconstruction from Images with 3D Gaussian Splatting
DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation
RaSA: Rank-Sharing Low-Rank Adaptation
Small Transformers, Big Results: Efficient Diffusion with Parameter Sharing
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries
Learning Label Encodings for Deep Regression
Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning
A Dynamic Prompt-tuning Method for Data Augmentation with Associated Knowledge
On Computation and Generalization of Generative Adversarial Networks under Spectrum Control
Rare event modeling with self-regularized normalizing flows: what can we learn from a single failure?
Achieve the Minimum Width of Neural Networks for Universal Approximation
Federated Learning with Variational Autoencoders
PAC Prediction Sets Under Covariate Shift
A Multi-Level Framework for Accelerating Training Transformer Models
Synthetic Labeling: A Novel Approach to Advancing Few-Shot Learning
GNN-LM: Language Modeling based on Global Contexts via GNN
Adversarial Examples for Semantic Image Segmentation
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting
EgoSim: Egocentric Exploration in Virtual Worlds with Multi-modal Conditioning
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach
Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis
MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods
Fast Feedforward 3D Gaussian Splatting Compression
Fairness and Accuracy under Domain Generalization
DAWN: Dynamic Frame Avatar with Non-autoregressive Diffusion Framework for Talking head Video Generation
Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design
Learning under Temporal Label Noise
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning
Bridging Recommendation and Marketing via Recurrent Intensity Modeling
Shallow and Deep Networks are Near-Optimal Approximators of Korobov Functions
SpinQuant: LLM Quantization with Learned Rotations
Localizing and Editing Knowledge In Text-to-Image Generative Models
Measuring and Improving the Use of Graph Information in Graph Neural Networks
Continuous Exposure Learning for Low-light Image Enhancement using Neural ODEs
Towards counterfactual fairness through auxiliary variables
Visual Representation Learning over Latent Domains
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models
CompOFA - Compound Once-For-All Networks for Faster Multi-Platform Deployment
FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets
Information-Theoretic Analysis of Unsupervised Domain Adaptation
Interpretable Unsupervised Diversity Denoising and Artefact Removal
Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input
Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning
ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge
A Data-Driven Measure of Relative Uncertainty for Misclassification Detection
Multi-Label Node Classification with Label Influence Propagation
TestGenEval: A Real World Unit Test Generation and Test Completion Benchmark
Learning a Natural Language Interface with Neural Programmer
Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning
Constraint-Free Structure Learning with Smooth Acyclic Orientations
Revisiting CounteRGAN for Counterfactual Explainability of Graphs
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation
Stabilized Medical Image Attacks
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
RETHINKING POSITIONAL EMBEDDING: A CASE STUDY IN TEMPORAL EVENT SEQUENCE MODELLING
A Branching Decoder for Set Generation
Understanding and Mitigating Hallucination in Large Vision-Language Models via Modular Attribution and Intervention
Imbalanced Semi-supervised Learning with Bias Adaptive Classifier
Learning from others' mistakes: Avoiding dataset biases without modeling them
Curvature Graph Network
Bayesian Incremental Learning for Deep Neural Networks
Deep Anomaly Detection with Outlier Exposure
Option Discovery using Deep Skill Chaining
Class Distribution-induced Attention Map for Open-vocabulary Semantic Segmentations
Convergent Graph Solvers
Deep Layers as Stochastic Solvers
Almost Sure Last Iterate Convergence of Sharpness-Aware Minimization
Graphical Multioutput Gaussian Process with Attention
Decoding Decoders: Finding Optimal Representation Spaces for Unsupervised Similarity Tasks
Uncertainty Sets for Image Classifiers using Conformal Prediction
Diversity is All You Need: Learning Skills without a Reward Function
Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning
Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation
Neural Rate Control for Learned Video Compression
Neural ODE Processes
Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models
Support Regularized Sparse Coding and Its Fast Encoder
Avoiding spurious correlations via logit correction
EmerDiff: Emerging Pixel-level Semantic Knowledge in Diffusion Models
Unsupervised Model Tree Heritage Recovery
EQA-MX: Embodied Question Answering using Multimodal Expression
SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement
Batch Policy Gradient Methods for Improving Neural Conversation Models
Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning
A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
Provable Robust Watermarking for AI-Generated Text
GridMix: Exploring Spatial Modulation for Neural Fields in PDE Modeling
Causal Confusion and Reward Misidentification in Preference-Based Reward Learning
Consistency-guided Prompt Learning for Vision-Language Models
Policy Expansion for Bridging Offline-to-Online Reinforcement Learning
Depthwise Separable Convolutions for Neural Machine Translation
UIFace: Unleashing Inherent Model Capabilities to Enhance Intra-Class Diversity in Synthetic Face Recognition
Adjustable Real-time Style Transfer
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
Long Range Arena : A Benchmark for Efficient Transformers
Intriguing Properties of Generative Classifiers
Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions
MoS: Unleashing Parameter Efficiency of Low-Rank Adaptation with Mixture of Shards
A Kernel Random Matrix-Based Approach for Sparse PCA
Video Action Differencing
Federated Adversarial Domain Adaptation
Spatially Parallel Convolutions
Near-optimal Coresets for Robust Clustering
Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures
Find A Winning Sign: Sign Is All We Need to Win the Lottery
Deconstructing Denoising Diffusion Models for Self-Supervised Learning
LiveXiv - A Multi-Modal live benchmark based on Arxiv papers content
Diagnosing and Rectifying Vision Models using Language
NAM - Unsupervised Cross-Domain Image Mapping without Cycles or GANs
From $t$-SNE to UMAP with contrastive learning
Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism
Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation
ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
Amortizing intractable inference in large language models
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models
Revisiting Design Choices in Offline Model Based Reinforcement Learning
Frequency-Guided Masking for Enhanced Vision Self-Supervised Learning
MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning
Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning
Active Learning for Neural PDE Solvers