yusuke1997/dblp-id-title huggingface dataset:
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis
Progressive distillation induces an implicit curriculum
Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language Models
Machine Unlearning of Federated Clusters
Geometric Implications of Classification on Reducing Open Space Risk
Self-supervised Representation Learning with Relative Predictive Coding
Neurosymbolic Grounding for Compositional World Models
Data-Independent Neural Pruning via Coresets
FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling
Neural Networks as Kernel Learners: The Silent Alignment Effect
Sylber: Syllabic Embedding Representation of Speech from Raw Audio
Provable Robustness against Wasserstein Distribution Shifts via Input Randomization
Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement Learning
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein
X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback
Learning Efficient Positional Encodings with Graph Neural Networks
Efficient Edge Inference by Selective Query
Data Poisoning Won't Save You From Facial Recognition
Variational Bayesian Last Layers
When Attention Sink Emerges in Language Models: An Empirical View
An Online Learning Theory of Trading-Volume Maximization
Mid-Vision Feedback
GTR: Improving Large 3D Reconstruction Models through Geometry and Texture Refinement
Rigid Protein-Protein Docking via Equivariant Elliptic-Paraboloid Interface Prediction
No MCMC for me: Amortized sampling for fast and stable training of energy-based models
Cascade Adversarial Machine Learning Regularized with a Unified Embedding
Proactive Multi-Camera Collaboration for 3D Human Pose Estimation
Relational State-Space Model for Stochastic Multi-Object Systems
Latent Neural ODEs with Sparse Bayesian Multiple Shooting
Learning Splitting Heuristics in Divide-and-Conquer SAT Solvers with Reinforcement Learning
DKM: Differentiable k-Means Clustering Layer for Neural Network Compression
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
PeriodWave: Multi-Period Flow Matching for High-Fidelity Waveform Generation
Relation-Aware Diffusion for Heterogeneous Graphs with Partially Observed Features
Prediction and generalisation over directed actions by grid cells
CUTS: Neural Causal Discovery from Irregular Time-Series Data
A Self-Attention Ansatz for Ab-initio Quantum Chemistry
Ranking Policy Gradient
Is Your Multimodal Language Model Oversensitive to Safe Queries?
BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion
Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities
Towards "AlphaChem": Chemical Synthesis Planning with Tree Search and Deep Neural Network Policies
Semi-relaxed Gromov-Wasserstein divergence and applications on graphs
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
NVS-Solver: Video Diffusion Model as Zero-Shot Novel View Synthesizer
Bayesian Policy Optimization for Model Uncertainty
Do Generated Data Always Help Contrastive Learning?
OMG: Opacity Matters in Material Modeling with Gaussian Splatting
Constrained Policy Optimization via Bayesian World Models
Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis
PvNeXt: Rethinking Network Design and Temporal Motion for Point Cloud Video Recognition
Endowing Visual Reprogramming with Adversarial Robustness
Your Mixture-of-Experts LLM Is Secretly an Embedding Model for Free
Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems
An Explanation of In-context Learning as Implicit Bayesian Inference
Protein Discovery with Discrete Walk-Jump Sampling
Latent Space Chain-of-Embedding Enables Output-free LLM Self-Evaluation
Deep Nets Don't Learn via Memorization
Fair and Efficient Contribution Valuation for Vertical Federated Learning
Enhanced Face Recognition using Intra-class Incoherence Constraint
How gradient estimator variance and bias impact learning in neural networks
Bit-Pragmatic Deep Neural Network Computing
Enhancing Transformation-Based Defenses Against Adversarial Attacks with a Distribution Classifier
Skill or Luck? Return Decomposition via Advantage Functions
Churn Reduction via Distillation
Predict then Propagate: Graph Neural Networks meet Personalized PageRank
Can Text Encoders be Deceived by Length Attack?
Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning
Joint Multimodal Learning with Deep Generative Models
Action Sequence Augmentation for Action Anticipation
gRNAde: Geometric Deep Learning for 3D RNA inverse design
Do deep networks transfer invariances across classes?
Unsupervised Cipher Cracking Using Discrete GANs
DiTTo-TTS: Diffusion Transformers for Scalable Text-to-Speech without Domain-Specific Factors
Interpretable Causal Representation Learning for Biological Data in the Pathway Space
ReinforceWalk: Learning to Walk in Graph with Monte Carlo Tree Search
Imposing Category Trees Onto Word-Embeddings Using A Geometric Construction
Cafe-Talk: Generating 3D Talking Face Animation with Multimodal Coarse- and Fine-grained Control
The Generalization Gap in Offline Reinforcement Learning
DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning
On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?
Linear Convergent Decentralized Optimization with Compression
Graph Sparsification via Mixture of Graphs
Predicting Classification Accuracy When Adding New Unobserved Classes
Test-time Adaptation for Cross-modal Retrieval with Query Shift
Out-of-distribution Detection with Implicit Outlier Transformation
GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation
Artificial Neuronal Ensembles with Learned Context Dependent Gating
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs
Syntax-Directed Variational Autoencoder for Structured Data
Gray-Box Gaussian Processes for Automated Reinforcement Learning
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks
Knowledge Graph Finetuning Enhances Knowledge Manipulation in Large Language Models
Spherical CNNs
Sparse Autoencoders Find Highly Interpretable Features in Language Models
MPCFORMER: Fast, Performant and Provate Transformer Inference with MPC
Mixed Precision Training
Unveiling the Magic of Code Reasoning through Hypothesis Decomposition and Amendment
SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum
Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning
Neural Phylogeny: Fine-Tuning Relationship Detection among Neural Networks
Learning-Augmented Search Data Structures
Understanding Latent Correlation-Based Multiview Learning and Self-Supervision: An Identifiability Perspective
Sparse Coding with Gated Learned ISTA
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
Algorithmic Stability Based Generalization Bounds for Adversarial Training
Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes
Proving the Lottery Ticket Hypothesis for Convolutional Neural Networks
Anisotropic Random Feature Regression in High Dimensions
DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder
Generating Multiple Objects at Spatially Distinct Locations
LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations
CubeDiff: Repurposing Diffusion-Based Image Models for Panorama Generation
Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation
Out-Of-Domain Unlabeled Data Improves Generalization
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates
Noise Is Not the Main Factor Behind the Gap Between Sgd and Adam on Transformers, But Sign Descent Might Be
Diving Segmentation Model into Pixels
Prompt Programming for the Visual Domain
Dual Lottery Ticket Hypothesis
PIN: Prolate Spheroidal Wave Function-based Implicit Neural Representations
Toward Student-oriented Teacher Network Training for Knowledge Distillation
Explaining Image Classifiers by Counterfactual Generation
A Fast and Provable Algorithm for Sparse Phase Retrieval
Building Math Agents with Multi-Turn Iterative Preference Learning
LiftPool: Bidirectional ConvNet Pooling
On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks
Cauchy-Schwarz Divergence Information Bottleneck for Regression
MambaExtend: A Training-Free Approach to Improve Long Context Extension of Mamba
Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations
AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights
A Neural Framework for Generalized Causal Sensitivity Analysis
From Decoupling to Adaptive Transformation: a Wider Optimization Space for PTQ
Layer Swapping for Zero-Shot Cross-Lingual Transfer in Large Language Models
MultiViz: Towards Visualizing and Understanding Multimodal Models
Neural Relational Inference with Node-Specific Information
ParetoFlow: Guided Flows in Multi-Objective Optimization
ReCogLab: a framework testing relational reasoning & cognitive hypotheses on LLMs
Adaptive Quantization of Neural Networks
Sharpness-Aware Black-Box Optimization
A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery
Effective and Efficient Vote Attack on Capsule Networks
Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks
In-context Autoencoder for Context Compression in a Large Language Model
Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models
Training Data Generating Networks: Shape Reconstruction via Bi-level Optimization
ZooProbe: A Data Engine for Evaluating, Exploring, and Evolving Large-scale Training Data for Multimodal LLMs
Neural Networks for Learning Counterfactual G-Invariances from Single Environments
Disjoint Mapping Network for Cross-modal Matching of Voices and Faces
Multi-agent Reinforcement Learning for Networked System Control
Asymmetric Factorized Bilinear Operation for Vision Transformer
How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions
Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace
PnP Inversion: Boosting Diffusion-based Editing with 3 Lines of Code
Practical Integration via Separable Bijective Networks
CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery
Optimistic Bayesian Optimization with Unknown Constraints
Orbit-Equivariant Graph Neural Networks
Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders
I2AM: Interpreting Image-to-Image Latent Diffusion Models via Bi-Attribution Maps
Scaling Up Probabilistic Circuits by Latent Variable Distillation
Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning
Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo
Dynamic Modeling of Patients, Modalities and Tasks via Multi-modal Multi-task Mixture of Experts
Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model
HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models
Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data
Local-Prompt: Extensible Local Prompts for Few-Shot Out-of-Distribution Detection
RMP-SAM: Towards Real-Time Multi-Purpose Segment Anything
Conditional Learning of Fair Representations
Are wider nets better given the same number of parameters?
Convolutional Sequence Modeling Revisited
miniCTX: Neural Theorem Proving with (Long-)Contexts
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling
The Ramanujan Library - Automated Discovery on the Hypergraph of Integer Relations
Adversarially robust transfer learning
Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learning
Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game
Neural Control System for Continuous Glucose Monitoring and Maintenance
PF-GNN: Differentiable particle filtering based approximation of universal graph representations
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation
A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning
Self-Evolving Multi-Agent Collaboration Networks for Software Development
Disparate Impact in Differential Privacy from Gradient Misalignment
Omnigrok: Grokking Beyond Algorithmic Data
Learning Synthetic Environments and Reward Networks for Reinforcement Learning
CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents
GenDataAgent: On-the-fly Dataset Augmentation with Synthetic Data
Neural gradients are near-lognormal: improved quantized and sparse training
Neural Program Search: Solving Programming Tasks from Description and Examples
Group Equivariant Generative Adversarial Networks
Offline Hierarchical Reinforcement Learning via Inverse Optimization
Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation
High-Precision Dichotomous Image Segmentation via Probing Diffusion Capacity
Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees
Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies
On the Uncomputability of Partition Functions in Energy-Based Sequence Models
Scalable and Order-robust Continual Learning with Additive Parameter Decomposition
RNNs are not Transformers (Yet): The Key Bottleneck on In-Context Retrieval
Remove Symmetries to Control Model Expressivity and Improve Optimization
Automated Relational Meta-learning
Tag2Text: Guiding Vision-Language Model via Image Tagging
Mitigating the Curse of Dimensionality for Certified Robustness via Dual Randomized Smoothing
RobustKV: Defending Large Language Models against Jailbreak Attacks via KV Eviction
Understanding Generalization in Recurrent Neural Networks
TexTailor: Customized Text-aligned Texturing via Effective Resampling
Auxiliary Variational MCMC
Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling
Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations
Supervised Policy Update for Deep Reinforcement Learning
Training with Quantization Noise for Extreme Model Compression
STAMP: Scalable Task- And Model-agnostic Collaborative Perception
Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures
Go with the flow: Adaptive control for Neural ODEs
Uncertainty-Aware Decoding with Minimum Bayes Risk
Neural Epitome Search for Architecture-Agnostic Network Compression
Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees
Decoupling regularization from the action space
Horizon Generalization in Reinforcement Learning
Short and Sparse Deconvolution - A Geometric Approach
Quantifying the Plausibility of Context Reliance in Neural Machine Translation
Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness
Temporal Ensembling for Semi-Supervised Learning
OS-ATLAS: Foundation Action Model for Generalist GUI Agents
Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent
Universal Humanoid Motion Representations for Physics-Based Control
Equivariant Hypergraph Diffusion Neural Operators
The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models
Meta-prediction Model for Distillation-Aware NAS on Unseen Datasets
Towards Effective and Interpretable Human-Agent Collaboration in MOBA Games: A Communication Perspective
EffoVPR: Effective Foundation Model Utilization for Visual Place Recognition
Probabilistic Neural Pruning via Sparsity Evolutionary Fokker-Planck-Kolmogorov Equation
Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval
Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models
Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective
Semantic Temporal Abstraction via Vision-Language Model Guidance for Efficient Reinforcement Learning
A DIRT-T Approach to Unsupervised Domain Adaptation
LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch
Lifelong Perceptual Programming By Example
Universal Vision-Language Dense Retrieval: Learning A Unified Representation Space for Multi-Modal Retrieval
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
Retrieval-Enhanced Contrastive Vision-Text Models
Effective Structural Encodings via Local Curvature Profiles
Denoising Autoregressive Transformers for Scalable Text-to-Image Generation
VA-RED2: Video Adaptive Redundancy Reduction
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain
A Theoretical Framework for Inference and Learning in Predictive Coding Networks
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?
Federated Learning for Local and Global Data Distribution
PRDP: Progressively Refined Differentiable Physics
MOTOR: A Time-to-Event Foundation Model For Structured Medical Records
AVHBench: A Cross-Modal Hallucination Benchmark for Audio-Visual Large Language Models
HQGS: High-Quality Novel View Synthesis with Gaussian Splatting in Degraded Scenes
DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR
MaskGAN: Better Text Generation via Filling in the _______
Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Generalization bounds for deep convolutional neural networks
EControl: Fast Distributed Optimization with Compression and Error Control
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks
An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression
B-Spline CNNs on Lie groups
Weakly Supervised Explainable Phrasal Reasoning with Neural Fuzzy Logic
Learning Graphical State Transitions
Multilingual Neural Machine Translation with Knowledge Distillation
A Newborn Embodied Turing Test for Comparing Object Segmentation Across Animals and Machines
Robust Fair Clustering: A Novel Fairness Attack and Defense Framework
Improved Estimation of Concentration Under ℓp-Norm Distance Metrics Using Half Spaces
Large-scale and Fine-grained Vision-language Pre-training for Enhanced CT Image Understanding
Oracle efficient truncated statistics
Think Then React: Towards Unconstrained Action-to-Reaction Motion Generation
No Reason for No Supervision: Improved Generalization in Supervised Models
Distributed Bandit Learning: Near-Optimal Regret with Efficient Communication
Intelligent synapses for multi-task and transfer learning
Poison-splat: Computation Cost Attack on 3D Gaussian Splatting
Learning Expensive Coordination: An Event-Based Deep RL Approach
Gradient Estimators for Implicit Models
Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model
The Consensus Game: Language Model Generation via Equilibrium Search
Global Convergence of Three-layer Neural Networks in the Mean Field Regime
Multi-Perspective Data Augmentation for Few-shot Object Detection
IGLU: Efficient GCN Training via Lazy Updates
FP-DETR: Detection Transformer Advanced by Fully Pre-training
DSPO: Direct Score Preference Optimization for Diffusion Model Alignment
Variance-Aware Sparse Linear Bandits
Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation
TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning
Harnessing Diversity for Important Data Selection in Pretraining Large Language Models
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
Personalized Federated Learning with First Order Model Optimization
Geometry Image Diffusion: Fast and Data-Efficient Text-to-3D with Image-Based Surface Representation
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models
Distilling Knowledge from Reader to Retriever for Question Answering
Aligning Visual Contrastive learning models via Preference Optimization
Superclass-Conditional Gaussian Mixture Model For Learning Fine-Grained Embeddings
Denoising Diffusion Bridge Models
MuHBoost: Multi-Label Boosting For Practical Longitudinal Human Behavior Modeling
Benchmarking Algorithms for Federated Domain Generalization
On Double Descent in Reinforcement Learning with LSTD and Random Features
Making LLaMA SEE and Draw with SEED Tokenizer
ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update
ALFWorld: Aligning Text and Embodied Environments for Interactive Learning
No Equations Needed: Learning System Dynamics Without Relying on Closed-Form ODEs
Economic Hyperparameter Optimization with Blended Search Strategy
A Fine-Tuning Approach to Belief State Modeling
Parameter-Efficient Multi-Task Model Fusion with Partial Linearization
PaCA: Partial Connection Adaptation for Efficient Fine-Tuning
Demystifying Inter-Class Disentanglement
A Structured Self-Attentive Sentence Embedding
New Insights on Reducing Abrupt Representation Change in Online Continual Learning
$\beta$-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap
BatchPrompt: Accomplish more with less
Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting
Investigating the Benefits of Projection Head for Representation Learning
Nonlinear ICA Using Volume-Preserving Transformations
Effectively Modeling Time Series with Simple Discrete State Spaces
Jensen-Shannon Divergence in Safe Multi- Agent RL
Multi-agent cooperation through learning-aware policy gradients
NASPY: Automated Extraction of Automated Machine Learning Models
Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks
Understanding weight-magnitude hyperparameters in training binary networks
Decoupled Weight Decay Regularization
Improving Automated Speech Recognition Using Retrieval-Based Voice Conversion
Top-label calibration and multiclass-to-binary reductions
SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation
SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series
Confronting Reward Model Overoptimization with Constrained RLHF
Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization
QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization
RGBD-GAN: Unsupervised 3D Representation Learning From Natural Image Datasets via RGBD Image Synthesis
Dichotomy of Control: Separating What You Can Control from What You Cannot
SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training
Contrastive Learning with Hard Negative Samples
Less is More: Fewer Interpretable Region via Submodular Subset Selection
Single-Photon Image Classification
SCoMoE: Efficient Mixtures of Experts with Structured Communication
CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping
DICE: End-to-end Deformation Capture of Hand-Face Interactions from a Single Image
Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers
Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration
Bundle Neural Network for message diffusion on graphs
Attentive Neural Processes