yusuke1997/dblp-id-title huggingface dataset:
Swift4D: Adaptive divide-and-conquer Gaussian Splatting for compact and efficient reconstruction of dynamic scene
SafeWatch: An Efficient Safety-Policy Following Video Guardrail Model with Transparent Explanations
Does Training with Synthetic Data Truly Protect Privacy?
Meta Temporal Point Processes
Unraveling the Key Components of OOD Generalization via Diversification
Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data
Agree to Disagree: Diversity through Disagreement for Better Transferability
Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds
GoBigger: A Scalable Platform for Cooperative-Competitive Multi-Agent Interactive Simulation
Improving the Convergence of Dynamic NeRFs via Optimal Transport
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
BENO: Boundary-embedded Neural Operators for Elliptic PDEs
An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning
Deep, Skinny Neural Networks are not Universal Approximators
Towards Fast Adaptation of Neural Architectures with Meta Learning
Exploring Active 3D Object Detection from a Generalization Perspective
i-RevNet: Deep Invertible Networks
Morphing Tokens Draw Strong Masked Image Models
A Temporal Kernel Approach for Deep Learning with Continuous-time Information
Deep Neural Networks as Gaussian Processes
On the Almost Sure Convergence of the Stochastic Three Points Algorithm
Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening
Average Sensitivity of Decision Tree Learning
Censoring Representations with Multiple-Adversaries over Random Subspaces
Multi-Agent Cooperation and the Emergence of (Natural) Language
A teacher-student framework to distill future trajectories
Multimodal Web Navigation with Instruction-Finetuned Foundation Models
Binary Losses for Density Ratio Estimation
ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis
Towards Understanding Generalization via Decomposing Excess Risk Dynamics
Set Prediction without Imposing Structure as Conditional Density Estimation
DS-LLM: Leveraging Dynamical Systems to Enhance Both Training and Inference of Large Language Models
ADMM for Structured Fractional Minimization
Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions
RECAST: Reparameterized, Compact weight Adaptation for Sequential Tasks
Learning with AMIGo: Adversarially Motivated Intrinsic Goals
Sample-Efficient Quality-Diversity by Cooperative Coevolution
Neural Causal Graph for Interpretable and Intervenable Classification
Parametrizing Product Shape Manifolds by Composite Networks
The impact of allocation strategies in subset learning on the expressive power of neural networks
Interactive Image Generation Using Scene Graphs
Learning from Between-class Examples for Deep Sound Recognition
CoT3DRef: Chain-of-Thoughts Data-Efficient 3D Visual Grounding
Brain decoding: toward real-time reconstruction of visual perception
Enhancing Prediction Performance through Influence Measure
Multi-objective Differentiable Neural Architecture Search
Democratizing Fine-grained Visual Recognition with Large Language Models
Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition
Back to the Future: predicting causal relationships influencing oil prices
Fortuitous Forgetting in Connectionist Networks
Locally Free Weight Sharing for Network Width Search
InfoGS: Efficient Structure-Aware 3D Gaussians via Lightweight Information Shaping
An operator preconditioning perspective on training in physics-informed machine learning
AnoLLM: Large Language Models for Tabular Anomaly Detection
Understanding l4-based Dictionary Learning: Interpretation, Stability, and Robustness
PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructions
Pyraformer: Low-Complexity Pyramidal Attention for Long-Range Time Series Modeling and Forecasting
Revisiting text-to-image evaluation with Gecko: on metrics, prompts, and human rating
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective
Batch Reinforcement Learning Through Continuation Method
Nonlinear model reduction for operator learning
AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents
Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
BERTScore: Evaluating Text Generation with BERT
CONDA: Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts
OvercookedV2: Rethinking Overcooked for Zero-Shot Coordination
Deep neuroethology of a virtual rodent
Generative Classifiers Avoid Shortcut Solutions
Neural Program Repair by Jointly Learning to Localize and Repair
On the relation between statistical learning and perceptual distances
Towards Stabilizing Batch Statistics in Backward Propagation of Batch Normalization
The Risks of Invariant Risk Minimization
BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection
Random matrices in service of ML footprint: ternary random features with no performance loss
Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness
Predictive Inverse Dynamics Models are Scalable Learners for Robotic Manipulation
Curiosity-driven Red-teaming for Large Language Models
On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data
FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes
Comparing Rewinding and Fine-tuning in Neural Network Pruning
OBI-Bench: Can LMMs Aid in Study of Ancient Script on Oracle Bones?
Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision?
Evaluating Impact of Emoticons and Pre-processing on Sentiment Classification of Translated African Tweets
EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data
Privacy Auditing of Large Language Models
System 1.x: Learning to Balance Fast and Slow Planning with Language Models
Stochastic Training is Not Necessary for Generalization
Diffusing States and Matching Scores: A New Framework for Imitation Learning
Scalable Unbalanced Optimal Transport using Generative Adversarial Networks
MetaXLR - Mixed Language Meta Representation Transformation for Low-resource Cross-lingual Learning based on Multi-Armed Bandit
Quadratic models for understanding catapult dynamics of neural networks
DiffSplat: Repurposing Image Diffusion Models for Scalable Gaussian Splat Generation
Composition-based Multi-Relational Graph Convolutional Networks
DiscoveryBench: Towards Data-Driven Discovery with Large Language Models
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
Backpropagation through Combinatorial Algorithms: Identity with Projection Works
Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain
Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning
ADef: an Iterative Algorithm to Construct Adversarial Deformations
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy
Learning to Select Nodes in Branch and Bound with Sufficient Tree Representation
Learning to Represent Programs with Property Signatures
SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition
Noise Injection Node Regularization for Robust Learning
When should agents explore?
Latent Variable Representation for Reinforcement Learning
MuPT: A Generative Symbolic Music Pretrained Transformer
AdAct: Learning to Optimize Activation Function Choice through Adaptive Activation Modules
Meta-Learning Deep Energy-Based Memory Models
Measuring the Reliability of Reinforcement Learning Algorithms
Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control
Neural Common Neighbor with Completion for Link Prediction
A General Framework for Off-Policy Learning with Partially-Observed Reward
Spectral Compressive Imaging via Unmixing-driven Subspace Diffusion Refinement
Isometric Transformation Invariant and Equivariant Graph Convolutional Networks
Automatic Chain of Thought Prompting in Large Language Models
Unsupervised Learning of Full-Waveform Inversion: Connecting CNN and Partial Differential Equation in a Loop
An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch
Illusory Attacks: Information-theoretic detectability matters in adversarial attacks
Artificial Intelligent Life: A New Perspective on Artificial General Intelligence
Matrix Manifold Neural Networks++
Understanding approximate and unrolled dictionary learning for pattern recovery
Incremental few-shot learning via vector quantization in deep embedded space
Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise
Automated Data Augmentations for Graph Classification
The Singular Values of Convolutional Layers
Curvature-Guided Dynamic Scale Networks for Multi-View Stereo
LongPO: Long Context Self-Evolution of Large Language Models through Short-to-Long Preference Optimization
Explaining the Learning Dynamics of Direct Feedback Alignment
Efficient Sparse-Winograd Convolutional Neural Networks
A Geometric Analysis of Deep Generative Image Models and Its Applications
Neural Multi-Objective Combinatorial Optimization via Graph-Image Multimodal Fusion
Combating Exacerbated Heterogeneity for Robust Models in Federated Learning
Trading Information between Latents in Hierarchical Variational Autoencoders
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings
Optimization inspired Multi-Branch Equilibrium Models
Deformable DETR: Deformable Transformers for End-to-End Object Detection
High-Quality Joint Image and Video Tokenization with Causal VAE
Anytime Dense Prediction with Confidence Adaptivity
Multimodal Unsupervised Domain Generalization by Retrieving Across the Modality Gap
Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint
VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation
Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection
P-Spikessm: Harnessing Probabilistic Spiking State Space Models for Long-Range Dependency Tasks
Bridging the Gap Between f-divergences and Bayes Hilbert Spaces
SeaFormer: Squeeze-enhanced Axial Transformer for Mobile Semantic Segmentation
Reset-Free Lifelong Learning with Skill-Space Planning
ANOCE: Analysis of Causal Effects with Multiple Mediators via Constrained Structural Learning
DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genomes
Reanalysis of Variance Reduced Temporal Difference Learning
FIGARO: Controllable Music Generation using Learned and Expert Features
COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery
MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning
Joint Fine-tuning and Conversion of Pretrained Speech and Language Models towards Linear Complexity
Adversarial Robustness Through the Lens of Causality
The Effectiveness of Transfer Learning in Electronic Health Records Data
Transferring Learning Trajectories of Neural Networks
Don't forget the nullspace! Nullspace occupancy as a mechanism for out of distribution failure
Temporal Coherent Test Time Optimization for Robust Video Classification
Towards Marginal Fairness Sliced Wasserstein Barycenter
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data
Evaluating Large Language Models through Role-Guide and Self-Reflection: A Comparative Study
Acceleration of Federated Learning with Alleviated Forgetting in Local Training
Advancing Image Classification through Parameter-Efficient Fine-Tuning: A Study on LoRA with Plant Disease Detection Datasets
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
Probing BERT in Hyperbolic Spaces
Training Language Models on Synthetic Edit Sequences Improves Code Synthesis
NutriBench: A Dataset for Evaluating Large Language Models in Nutrition Estimation from Meal Descriptions
In-context Exploration-Exploitation for Reinforcement Learning
DAG Learning on the Permutahedron
DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?
TFG-Flow: Training-free Guidance in Multimodal Generative Flow
Augmentation Component Analysis: Modeling Similarity via the Augmentation Overlaps
Plan-Based Relaxed Reward Shaping for Goal-Directed Tasks
ResFields: Residual Neural Fields for Spatiotemporal Signals
Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation
Transfer of View-manifold Learning to Similarity Perception of Novel Objects
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary
TRACE: Temporal Grounding Video LLM via Causal Event Modeling
MindSearch: Mimicking Human Minds Elicits Deep AI Searcher
Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization
RvS: What is Essential for Offline RL via Supervised Learning?
Neuron Platonic Intrinsic Representation From Dynamics Using Contrastive Learning
kNN-Diffusion: Image Generation via Large-Scale Retrieval
E-CRF: Embedded Conditional Random Field for Boundary-caused Class Weights Confusion in Semantic Segmentation
Basis Sharing: Cross-Layer Parameter Sharing for Large Language Model Compression
No More BLAH-BLAH: Embracing Real Text in the Image synthesis World
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer
Learning-Augmented $k$-means Clustering
Efficient Integrators for Diffusion Generative Models
Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model
Noisy Feature Mixup
Semi-Parametric Inducing Point Networks and Neural Processes
Reinforcement Learning for Control of Non-Markovian Cellular Population Dynamics
Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel
Deep Repulsive Clustering of Ordered Data Based on Order-Identity Decomposition
BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval
Bag of Tricks for Adversarial Training
The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation
Empirical Likelihood for Fair Classification
Dynamic Channel Pruning: Feature Boosting and Suppression
Equivariant Descriptor Fields: SE(3)-Equivariant Energy-Based Models for End-to-End Visual Robotic Manipulation Learning
Where Am I and What Will I See: An Auto-Regressive Model for Spatial Localization and View Prediction
L0-Sparse Canonical Correlation Analysis
Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
When do GFlowNets learn the right distribution?
Watermark Anything With Localized Messages
Hockey-Stick GAN
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam
TweedieMix: Improving Multi-Concept Fusion for Diffusion-based Image/Video Generation
Residual Deep Gaussian Processes on Manifolds
When Source-Free Domain Adaptation Meets Learning with Noisy Labels
CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding
T-WaveNet: A Tree-Structured Wavelet Neural Network for Time Series Signal Analysis
Representation Learning for Online and Offline RL in Low-rank MDPs
Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian
Implicit Regularization for Group Sparsity
A Fine-Grained Analysis on Distribution Shift
How Important is a Neuron
Recitation-Augmented Language Models
Diffusion Scattering Transforms on Graphs
Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection
Diffusion-based Decoupled Deterministic and Uncertain Framework for Probabilistic Multivariate Time Series Forecasting
Transformers Handle Endogeneity in In-Context Linear Regression
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective
Towards Poisoning Fair Representations
Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective
Deep Learning with Logged Bandit Feedback
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction
TODO: Enhancing LLM Alignment with Ternary Preferences
Neural Optimal Transport
Differentiation of Blackbox Combinatorial Solvers
Bounds on Lp Errors in Density Ratio Estimation via f-Divergence Loss Functions
Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision?
Risk-Sensitive Variational Actor-Critic: A Model-Based Approach
Graph-Relational Domain Adaptation
Confidence Elicitation: A New Attack Vector for Large Language Models
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary
Advantage-Guided Distillation for Preference Alignment in Small Language Models
MAESTRO: Masked Encoding Set Transformer with Self-Distillation
Deep Random Splines for Point Process Intensity Estimation
IOT: Instance-wise Layer Reordering for Transformer Structures
Optimal Transport for Offline Imitation Learning
On the Learnability of Watermarks for Language Models
Self-Monitoring Navigation Agent via Auxiliary Progress Estimation
Learnable Graph Convolutional Attention Networks
Policy Gradients Incorporating the Future
Monte-Carlo Planning and Learning with Language Action Value Estimates
Your classifier is secretly an energy based model and you should treat it like one
Latent Graph Inference using Product Manifolds
Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
QERA: an Analytical Framework for Quantization Error Reconstruction
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers
Transformers Provably Learn Two-Mixture of Linear Classification via Gradient Flow
SINGAPO: Single Image Controlled Generation of Articulated Parts in Objects
Controllable Generation via Locally Constrained Resampling
Training-Free Message Passing for Learning on Hypergraphs
Exploiting Class Activation Value for Partial-Label Learning
Latent Variable Sequential Set Transformers for Joint Multi-Agent Motion Prediction
Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning
DSF-GAN: Downstream Feedback Generative Adversarial Network
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
A Little Goes a Long Way: Efficient Long Context Training and Inference with Partial Contexts
Rotamer Density Estimator is an Unsupervised Learner of the Effect of Mutations on Protein-Protein Interaction
Poly-encoders: Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring
Neural Link Prediction with Walk Pooling
From Intervention to Domain Transportation: A Novel Perspective to Optimize Recommendation
Saliency is a Possible Red Herring When Diagnosing Poor Generalization
MA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions
Variational Autoencoders with Jointly Optimized Latent Dependency Structure
Offline bilingual word vectors, orthogonal transformations and the inverted softmax
Supervised Community Detection with Line Graph Neural Networks
A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs
What Is Missing in IRM Training and Evaluation? Challenges and Solutions
Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models
Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation
How Feature Learning Can Improve Neural Scaling Laws
Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning
Random Is All You Need: Random Noise Injection on Feature Statistics for Generalizable Deep Image Denoising
Improved Sampling Algorithms for Lévy-Itô Diffusion Models
ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
CrossBeam: Learning to Search in Bottom-Up Program Synthesis
Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models
Reasoning with Latent Diffusion in Offline Reinforcement Learning
Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting
MotherNet: Fast Training and Inference via Hyper-Network Transformers
GeoSeq2Seq: Information Geometric Sequence-to-Sequence Networks
Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport
Meta-Learning Update Rules for Unsupervised Representation Learning
Machine Comprehension Using Match-LSTM and Answer Pointer
Adversarial AutoAugment
Why Deep Neural Networks for Function Approximation?
Beyond task performance: evaluating and reducing the flaws of large multimodal models with in-context-learning
Learning Robust State Abstractions for Hidden-Parameter Block MDPs
Fiddler: CPU-GPU Orchestration for Fast Inference of Mixture-of-Experts Models
Symbol as Points: Panoptic Symbol Spotting via Point-based Representation
A Differentiable Physics Engine for Deep Learning in Robotics
Measuring memorization in RLHF for code completion
MAST: model-agnostic sparsified training
Judge Decoding: Faster Speculative Sampling Requires Going Beyond Model Alignment
Agent-based Graph Neural Networks
Learning Parametrised Graph Shift Operators
MARS: Markov Molecular Sampling for Multi-objective Drug Discovery
Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning
A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training
DeepNCM: Deep Nearest Class Mean Classifiers
Diffusion Feedback Helps CLIP See Better
Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
ChiroDiff: Modelling chirographic data with Diffusion Models
Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit
Learning Task-General Representations with Generative Neuro-Symbolic Modeling
Multi-class classification without multi-class labels
Online epsilon Net & Piercing Set for Geometric Concepts
SonicSim: A customizable simulation platform for speech processing in moving sound source scenarios
Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks
Statistical Tractability of Off-policy Evaluation of History-dependent Policies in POMDPs
Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement Learning
Fake It Till Make It: Federated Learning with Consensus-Oriented Generation
Teaching LLMs How to Learn with Contextual Fine-Tuning
Unsupervised Demixing of Structured Signals from Their Superposition Using GANs
Discovering modular solutions that generalize compositionally
The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization
Latent 3D Graph Diffusion
How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features
FairBatch: Batch Selection for Model Fairness
Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding
Tight Rates in Supervised Outlier Transfer Learning
DistillHGNN: A Knowledge Distillation Approach for High-Speed Hypergraph Neural Networks
On the Data-Efficiency with Contrastive Image Transformation in Reinforcement Learning
Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control
SysBench: Can LLMs Follow System Message?
Interpretability with full complexity by constraining feature information
Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference
CUDA: Curriculum of Data Augmentation for Long-tailed Recognition
Predicting the Generalization Gap in Deep Networks with Margin Distributions
Information Laundering for Model Privacy
Smoothing the Geometry of Probabilistic Box Embeddings
Tradeoffs in Data Augmentation: An Empirical Study
Revisiting Random Walks for Learning on Graphs
Generating Diverse High-Resolution Images with VQ-VAE
F3Set: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
A Simple Neural Attentive Meta-Learner