yusuke1997/dblp-id-title huggingface dataset:
CREIMBO: Cross-Regional Ensemble Interactions in Multi-view Brain Observations
Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs
Mixed-curvature Variational Autoencoders
Learning from Unlabelled Videos Using Contrastive Predictive Neural 3D Mapping
UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science
Wavelet Pooling for Convolutional Neural Networks
CollabEdit: Towards Non-destructive Collaborative Knowledge Editing
Signing the Supermask: Keep, Hide, Invert
MetaUrban: An Embodied AI Simulation Platform for Urban Micromobility
DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector
InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation
Test-Time Robust Personalization for Federated Learning
Omni-Dimensional Dynamic Convolution
Inductive representation learning on temporal graphs
A Novel Window-Interaction Module Based on W-MSA
Subgraph Federated Learning for Local Generalization
Relational Attention: Generalizing Transformers for Graph-Structured Tasks
ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning
Accelerated Single-Call Methods for Constrained Min-Max Optimization
Structuring Benchmark into Knowledge Graphs to Assist Large Language Models in Retrieving and Designing Models
Debiased Collaborative Filtering with Kernel-Based Causal Balancing
KinPFN: Bayesian Approximation of RNA Folding Kinetics using Prior-Data Fitted Networks
Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models
Federated Learning from Small Datasets
Inverse Constitutional AI: Compressing Preferences into Principles
Simple Spectral Graph Convolution
NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning
On Representing Linear Programs by Graph Neural Networks
Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems
Transferable Unlearnable Examples
SIM: Surface-based fMRI Analysis for Inter-Subject Multimodal Decoding from Movie-Watching Experiments
DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text
Reconsidering Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs
Self-Supervised Dataset Distillation for Transfer Learning
Contrastive Learning with Adversarial Perturbations for Conditional Text Generation
Pre-training via Denoising for Molecular Property Prediction
MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance
BayesOpt Adversarial Attack
Online Multi-Task Learning Using Active Sampling
Unsupervised and Scalable Algorithm for Learning Node Representations
Performance Analysis of a quantum-Classical Hybrid Reinforcement Learning Approach
Second-Order Fine-Tuning without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer
Revisiting Dynamic Convolution via Matrix Decomposition
Elucidating the Preconditioning in Consistency Distillation
A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference
When is a Convolutional Filter Easy to Learn?
ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding
Discrete Natural Evolution Strategies
Offline Model-Based Optimization by Learning to Rank
Guide Actor-Critic for Continuous Control
Multi-Mode Deep Matrix and Tensor Factorization
Acting in Delayed Environments with Non-Stationary Markov Policies
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Student-Informed Teacher Training
Monet: Mixture of Monosemantic Experts for Transformers
One For All: Towards Training One Graph Model For All Classification Tasks
SpeechTokenizer: Unified Speech Tokenizer for Speech Language Models
Locally Connected Echo State Networks for Time Series Forecasting
Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition
Near-optimal Policy Identification in Active Reinforcement Learning
Generalization and Distributed Learning of GFlowNets
Class Probability Matching with Calibrated Networks for Label Shift Adaption
Gradientless Descent: High-Dimensional Zeroth-Order Optimization
InfoBot: Transfer and Exploration via the Information Bottleneck
Scalable Sampling for Nonsymmetric Determinantal Point Processes
Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning
Causal Estimation for Text Data with (Apparent) Overlap Violations
DartControl: A Diffusion-Based Autoregressive Motion Model for Real-Time Text-Driven Motion Control
A Simple and Scalable Representation for Graph Generation
Large Language Models can Become Strong Self-Detoxifiers
BrainACTIV: Identifying visuo-semantic properties driving cortical selectivity using diffusion-based image manipulation
PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback
MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures
Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings
Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling
Causal Representation Learning from Multimodal Biomedical Observations
Consistent Video-to-Video Transfer Using Synthetic Dataset
Differentiable Mathematical Programming for Object-Centric Representation Learning
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning
Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders
Generalized Policy Iteration using Tensor Approximation for Hybrid Control
The MultiBERTs: BERT Reproductions for Robustness Analysis
Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
More or Less: When and How to Build Convolutional Neural Network Ensembles
Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets
LabelDP-Pro: Learning with Label Differential Privacy via Projections
Building a Subspace of Policies for Scalable Continual Learning
Investigating Pattern Neurons in Urban Time Series Forecasting
Geometrically regularized autoencoders for non-Euclidean data
MagicPIG: LSH Sampling for Efficient LLM Generation
Near, far: Patch-ordering enhances vision foundation models' scene understanding
Effective Distributed Learning with Random Features: Improved Bounds and Algorithms
Interactive Portrait Harmonization
Black-Box Adversarial Attack with Transferable Model-based Embedding
Which Tasks Should Be Compressed Together? A Causal Discovery Approach for Efficient Multi-Task Representation Compression
MovieDreamer: Hierarchical Generation for Coherent Long Visual Sequences
Multi-domain image generation and translation with identifiability guarantees
Diffusion Models are Evolutionary Algorithms
Generating Sequences by Learning to Self-Correct
Neuro-Symbolic Procedural Planning with Commonsense Prompting
Discrete Codebook World Models for Continuous Control
On the expressiveness and spectral bias of KANs
Generalized Variational Continual Learning
Variational Template Machine for Data-to-Text Generation
Provably Efficient Lifelong Reinforcement Learning with Linear Representation
Learning Continually by Spectral Regularization
Preble: Efficient Distributed Prompt Scheduling for LLM Serving
Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment
Conformal Prediction Sets Can Cause Disparate Impact
What's in a Prior? Learned Proximal Networks for Inverse Problems
Machine Unlearning for Image-to-Image Generative Models
LanczosNet: Multi-Scale Deep Graph Convolutional Networks
CryoGEN: Generative Energy-based Models for Cryogenic Electron Tomography Reconstruction
Guiding Policies with Language via Meta-Learning
Ancestral protein sequence reconstruction using a tree-structured Ornstein-Uhlenbeck variational autoencoder
Adaptive backtracking line search
ImagineNav: Prompting Vision-Language Models as Embodied Navigator through Scene Imagination
Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data
Estimating informativeness of samples with Smooth Unique Information
An Actor-Critic Algorithm for Sequence Prediction
Time-Agnostic Prediction: Predicting Predictable Video Frames
How Benign is Benign Overfitting ?
Deep Signature: Characterization of Large-Scale Molecular Dynamics
Neural Program Planner for Structured Predictions
Large Convolutional Model Tuning via Filter Subspace
Improved Probabilistic Image-Text Representations
Quantized Compressed Sensing with Score-Based Generative Models
Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
Emergent mechanisms for long timescales depend on training curriculum and affect performance in memory tasks
On the Turing Completeness of Modern Neural Network Architectures
Uni-Mol: A Universal 3D Molecular Representation Learning Framework
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication
Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models
Federated Class-Incremental Learning: A Hybrid Approach Using Latent Exemplars and Data-Free Techniques to Address Local and Global Forgetting
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Hessian-Free Online Certified Unlearning
Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring in Data
Depth separation and weight-width trade-offs for sigmoidal neural networks
Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference
Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments
Scale Mixtures of Neural Network Gaussian Processes
On the Optimal Memorization Power of ReLU Neural Networks
Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic
Logic and the 2-Simplicial Transformer
Distinguished In Uniform: Self-Attention Vs. Virtual Nodes
Rescaling Intermediate Features Makes Trained Consistency Models Perform Better
Resolution Attack: Exploiting Image Compression to Deceive Deep Neural Networks
AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval
On Calibration of LLM-based Guard Models for Reliable Content Moderation
Imitation Learning by Reinforcement Learning
Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution
On the Soft-Subnetwork for Few-Shot Class Incremental Learning
Winner's Curse? On Pace, Progress, and Empirical Rigor
Simulated+Unsupervised Learning With Adaptive Data Generation and Bidirectional Mappings
LLM Unlearning via Loss Adjustment with Only Forget Data
GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face Synthesis
Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback
Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusion
GOFA: A Generative One-For-All Model for Joint Graph Language Modeling
3D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation
LEAP: Liberate Sparse-View 3D Modeling from Camera Poses
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
Neuralized Markov Random Field for Interaction-Aware Stochastic Human Trajectory Prediction
Leveraging Flatness to Improve Information-Theoretic Generalization Bounds for SGD
On the Convergence of No-Regret Dynamics in Information Retrieval Games with Proportional Ranking Functions
Improving Differentiable Neural Architecture Search by Encouraging Transferability
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning
UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models
Personalized Representation from Personalized Generation
Topological Schrödinger Bridge Matching
Language Model Knowledge Distillation for Efficient Question Answering in Spanish
Machine Unlearning Fails to Remove Data Poisoning Attacks
Gradient-Based Neural DAG Learning
Single-agent Poisoning Attacks Suffice to Ruin Multi-Agent Learning
Copy is All You Need
In-Context Learning Learns Label Relationships but Is Not Conventional Learning
Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off
Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning
A Theory of Initialisation's Impact on Specialisation
Towards a Neural Statistician
Random mesh projectors for inverse problems
Solving Differential Equations with Constrained Learning
WebArena: A Realistic Web Environment for Building Autonomous Agents
Truly Generative Data Augmentation for Image Segmentation - Case of Cloud Images
Dataset Pruning: Reducing Training Data by Examining Generalization Influence
PatchDCT: Patch Refinement for High Quality Instance Segmentation
Efficient Model Editing with Task-Localized Sparse Fine-tuning
Critical Points of Linear Neural Networks: Analytical Forms and Landscape Properties
DyST: Towards Dynamic Neural Scene Representations on Real-World Videos
Meta-Continual Learning of Neural Fields
RPM: Generalizable Multi-Agent Policies for Multi-Agent Reinforcement Learning
Discovering Group Structures via Unitary Representation Learning
Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization
Discriminative Particle Filter Reinforcement Learning for Complex Partial observations
Understanding image motion with group representations
Conditional Contrastive Learning with Kernel
Demystifying Limited Adversarial Transferability in Automatic Speech Recognition Systems
A Dataset To Evaluate The Representations Learned By Video Prediction Models
Imitation Learning from Observations under Transition Model Disparity
Unknown Domain Inconsistency Minimization for Domain Generalization
Bridging the Gap between Variational Inference and Stochastic Gradient MCMC in Function Space
DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification
Analysis of Cosmic Microwave Background with Deep Learning
Neuromodulation Gated Transformer
Unlearning or Obfuscating? Jogging the Memory of Unlearned LLMs via Benign Relearning
Tuning Frequency Bias of State Space Models
STARC: A General Framework For Quantifying Differences Between Reward Functions
Recurrent Experience Replay in Distributed Reinforcement Learning
Neural Topic Model via Optimal Transport
Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark
Laplace Sample Information: Data Informativeness Through a Bayesian Lens
Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph
Efficient Temporal Denoising for Improved Depth Map Applications
Multi-Task Dense Predictions via Unleashing the Power of Diffusion
Synthetic continued pretraining
Representational Similarity via Interpretable Visual Concepts
A Decade's Battle on Dataset Bias: Are We There Yet?
RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards
AS-MLP: An Axial Shifted MLP Architecture for Vision
Linear Spherical Sliced Optimal Transport: A Fast Metric for Comparing Spherical Data
The KoLMogorov Test: Compression by Code Generation
From Probability to Counterfactuals: the Increasing Complexity of Satisfiability in Pearl's Causal Hierarchy
Glad: A Streaming Scene Generator for Autonomous Driving
Knowledge Distillation as Semiparametric Inference
Policy Optimization under Imperfect Human Interactions with Agent-Gated Shared Autonomy
Speech Robust Bench: A Robustness Benchmark For Speech Recognition
Learning How Not to Act in Text-based Games
Unbiased Teacher for Semi-Supervised Object Detection
DRESSing Up LLM: Efficient Stylized Question-Answering via Style Subspace Editing
Size-Generalizable RNA Structure Evaluation by Exploring Hierarchical Geometries
No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models
Average-case Acceleration for Bilinear Games and Normal Matrices
Parameter Space Noise for Exploration
An Empirical Study of the Effect of Background Data Size on the Stability of SHapley Additive exPlanations (SHAP) for Deep Learning Models
Learning rigid dynamics with face interaction graph networks
Is Your Video Language Model a Reliable Judge?
Delving into adversarial attacks on deep policies
Conformal Language Modeling
Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks
One Model Transfer to All: On Robust Jailbreak Prompts Generation against LLMs
Graph Contrastive Learning for Skeleton-based Action Recognition
Fair Resource Allocation in Federated Learning
Looking Backward: Streaming Video-to-Video Translation with Feature Banks
FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling
MGDA Converges under Generalized Smoothness, Provably
Attention-likelihood relationship in Transformers
Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering
Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis
Human Simulacra: Benchmarking the Personification of Large Language Models
signSGD via Zeroth-Order Oracle
Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
Attention layers provably solve single-location regression
Adversarial Discriminative Domain Adaptation (workshop extended abstract)
Is Attention All That NeRF Needs?
Benchmarks for Deep Off-Policy Evaluation
Harnessing Webpage UIs for Text-Rich Visual Understanding
Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching
Can CNNs Be More Robust Than Transformers?
Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation
RegMix: Data Mixture as Regression for Language Model Pre-training
VVC-Gym: A Fixed-Wing UAV Reinforcement Learning Environment for Multi-Goal Long-Horizon Problems
Compact Embedding of Binary-coded Inputs and Outputs using Bloom Filters
MR-GSM8K: A Meta-Reasoning Benchmark for Large Language Model Evaluation
Introspection: Accelerating Neural Network Training By Learning Weight Evolution
Capturing Human Category Representations by Sampling in Deep Feature Spaces
MixSATGEN: Learning Graph Mixing for SAT Instance Generation
PAD: Personalized Alignment of LLMs at Decoding-time
Global Convergence in Neural ODEs: Impact of Activation Functions
Predicate Hierarchies Improve Few-Shot State Classification
Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning
MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders
HGM³: Hierarchical Generative Masked Motion Modeling with Hard Token Mining
SeRA: Self-Reviewing and Alignment of LLMs using Implicit Reward Margins
Boltzmann priors for Implicit Transfer Operators
An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment
Lossless Compression of Structured Convolutional Models via Lifting
Number Cookbook: Number Understanding of Language Models and How to Improve It
From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation
Reproducing Meta-learning with differentiable closed-form solvers
Investigating Representations for Vision And Touch in Contact Rich Robot Scooping Tasks
Faster federated optimization under second-order similarity
Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation
Understanding new tasks through the lens of training data via exponential tilting
GSE: Group-wise Sparse and Explainable Adversarial Attacks
Transfer NAS with Meta-learned Bayesian Surrogates
RelaxLoss: Defending Membership Inference Attacks without Losing Utility
Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions
Towards Codable Watermarking for Injecting Multi-Bits Information to LLMs
Probabilistically Rewired Message-Passing Neural Networks
Process Reward Model with Q-value Rankings
Sample-Efficient Automated Deep Reinforcement Learning
VideoGrain: Modulating Space-Time Attention for Multi-Grained Video Editing
Poincare Glove: Hyperbolic Word Embeddings
Efficient Certified Defenses Against Patch Attacks on Image Classifiers
Semantic Loss Guided Data Efficient Supervised Fine Tuning for Safe Responses in LLMs
A critical analysis of self-supervision, or what we can learn from a single image
FOSP: Fine-tuning Offline Safe Policy through World Models
Neural tangent kernels, transportation mappings, and universal approximation
Part-Based Models Improve Adversarial Robustness
Decodable and Sample Invariant Continuous Object Encoder
Multimodal Quantitative Language for Generative Recommendation
Jointly Training Large Autoregressive Multimodal Models
Large Language Models are Efficient Learners of Noise-Robust Speech Recognition
Modeling content creator incentives on algorithm-curated platforms
Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting
Understanding Train-Validation Split in Meta-Learning with Neural Networks
ControlAR: Controllable Image Generation with Autoregressive Models
Generalization error of spectral algorithms
RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering
Learning Graph Quantized Tokenizers
Flash Inference: Near Linear Time Inference for Long Convolution Sequence Models and Beyond
MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection
Efficient Automated Circuit Discovery in Transformers using Contextual Decomposition
DPaI: Differentiable Pruning at Initialization with Node-Path Balance Principle
GravMAD: Grounded Spatial Value Maps Guided Action Diffusion for Generalized 3D Manipulation
Gradient Importance Learning for Incomplete Observations
Tracking the Copyright of Large Vision-Language Models through Parameter Learning Adversarial Images
Understanding over-squashing and bottlenecks on graphs via curvature
Wasserstein Embedding for Graph Learning
Erasing Concept Combination from Text-to-Image Diffusion Model
Spanning Tree-based Graph Generation for Molecules
Distilling Cognitive Backdoor Patterns within an Image
Human-Aligned Chess With a Bit of Search
Differentiable Scaffolding Tree for Molecule Optimization
MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision Transformer
DiCE: The Infinitely Differentiable Monte-Carlo Estimator
C-Learning: Learning to Achieve Goals via Recursive Classification
Selective Visual Representations Improve Convergence and Generalization for Embodied AI
Audio Super-Resolution using Neural Networks
Learning Disentangled Audio Representations through Controlled Synthesis
On the Fourier analysis in the SO(3) space : the EquiLoPO Network
Inference in probabilistic graphical models by Graph Neural Networks
Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems
AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation
A Theoretically-Principled Sparse, Connected, and Rigid Graph Representation of Molecules
ReDeEP: Detecting Hallucination in Retrieval-Augmented Generation via Mechanistic Interpretability
Treatment Effects Estimation By Uniform Transformer
Learning Harmonic Molecular Representations on Riemannian Manifold
Disentangling Content and Style via Unsupervised Geometry Distillation
Sharpness-Aware Minimization Enhances Feature Quality via Balanced Learning
Incorporating BERT into Neural Machine Translation
Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors
Combining Ensembles and Data Augmentation Can Harm Your Calibration
Quantifying Differences in Reward Functions
Accelerating Sinkhorn algorithm with sparse Newton iterations