yusuke1997/dblp-id-title huggingface dataset:
Fewer May Be Better: Enhancing Offline Reinforcement Learning with Reduced Dataset
The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting - An Analytical Model
Can Speculative Sampling Accelerate ReAct Without Compromising Reasoning Quality?
OGBench: Benchmarking Offline Goal-Conditioned RL
Latent-EnSF: A Latent Ensemble Score Filter for High-Dimensional Data Assimilation with Sparse Observation Data
Density-Preserving Heterogeneous Graph Sparsification for Representation Learning
What's In My Big Data?
Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism
A Meta-Learning Approach to Bayesian Causal Discovery
A Learning-based Iterative Method for Solving Vehicle Routing Problems
Hierarchical Generative Modeling for Controllable Speech Synthesis
Modulated Phase Diffusor: Content-Oriented Feature Synthesis for Detecting Unknown Objects
Model Extraction Attacks on Arabic BERT-Based APIs
Probing the Hidden Layers of a Music Generating Language Model
AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images
How Does Mixup Help With Robustness and Generalization?
Einops: Clear and Reliable Tensor Manipulations with Einstein-like Notation
Cross-Entropy Is All You Need To Invert the Data Generating Process
Should VLMs be Pre-trained with Image Data?
Learn to Select: Efficient Cross-device Federated Learning via Reinforcement Learning
Variance-based Gradient Compression for Efficient Distributed Deep Learning
K-HALU: Multiple Answer Korean Hallucination Benchmark for Large Language Models
Never Give Up: Learning Directed Exploration Strategies
7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019
Latent Sequence Decompositions
DIFFTACTILE: A Physics-based Differentiable Tactile Simulator for Contact-rich Robotic Manipulation
Adversarial Attacks on Neural Network Policies
On the interaction between supervision and self-play in emergent communication
Enhancing Graph Of Thought: Enhancing Prompts with LLM Rationales and Dynamic Temperature Control
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation
Wiring Up Vision: Minimizing Supervised Synaptic Updates Needed to Produce a Primate Ventral Stream
Learning to Act by Predicting the Future
Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning
Defining Expertise: Applications to Treatment Effect Estimation
Private Post-GAN Boosting
q-exponential family for policy optimization
Guiding Instruction-based Image Editing via Multimodal Large Language Models
Large Sparse Kernels for Federated Learning
Exponential Generalization Bounds with Near-Optimal Rates for $L_q$-Stable Algorithms
ADOPD: A Large-Scale Document Page Decomposition Dataset
Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models
Kronecker Mask and Interpretive Prompts are Language-Action Video Learners
AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly
Chemical-Reaction-Aware Molecule Representation Learning
AEVA: Black-box Backdoor Detection Using Adversarial Extreme Value Analysis
What Can Neural Networks Reason About?
Active Retrosynthetic Planning Aware of Route Quality
When LLMs Play the Telephone Game: Cultural Attractors as Conceptual Tools to Evaluate LLMs in Multi-turn Settings
Not All Language Model Features Are One-Dimensionally Linear
Quality-Similar Diversity via Population Based Reinforcement Learning
Ghost on the Shell: An Expressive Representation of General 3D Shapes
Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructions
2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Conference Track Proceedings
Semantic Aware Representation Learning for Lifelong Learning
Do 2D GANs Know 3D Shape? Unsupervised 3D Shape Reconstruction from 2D Image GANs
A Max-Affine Spline Perspective of Recurrent Neural Networks
TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series
Capability Localization: Capabilities Can be Localized rather than Individual Knowledge
BrainBERT: Self-supervised representation learning for intracranial recordings
Mirror Descent Policy Optimization
Benchmarking Predictive Coding Networks - Made Simple
Learning End-to-End Goal-Oriented Dialog
Initialization matters: Orthogonal Predictive State Recurrent Neural Networks
Case-based reasoning for better generalization in textual reinforcement learning
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck
Reward Model Ensembles Help Mitigate Overoptimization
Rethinking the Expressive Power of GNNs via Graph Biconnectivity
A transfer learning framework for weak to strong generalization
Elucidating the Exposure Bias in Diffusion Models
A Bi-Objective $\epsilon $-Constrained Framework for Quality-Cost Optimization in Language Model Ensembles
FedTMOS: Efficient One-Shot Federated Learning with Tsetlin Machine
Gradual Optimization Learning for Conformational Energy Minimization
Deep Orthogonal Hypersphere Compression for Anomaly Detection
Mitigating Parameter Interference in Model Merging via Sharpness-Aware Fine-Tuning
Exploring Weight Balancing on Long-Tailed Recognition Problem
L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data
Understanding the Stability-based Generalization of Personalized Federated Learning
Beyond Negativity: Re-Analysis and Follow-Up Experiments on Hope Speech Detection
Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot Classification
MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation
Test-time Adaptation for Regression by Subspace Alignment
FreCaS: Efficient Higher-Resolution Image Generation via Frequency-aware Cascaded Sampling
Graph Neural Network Guided Local Search for the Traveling Salesperson Problem
KiVA: Kid-inspired Visual Analogies for Testing Large Multimodal Models
The Update-Equivalence Framework for Decision-Time Planning
Revisit Micro-batch Clipping: Adaptive Data Pruning via Gradient Manipulation
Emergent Communication with Conversational Repair
Stochastic Bandits Robust to Adversarial Attacks
Learning Sparse Neural Networks through L_0 Regularization
Decision Information Meets Large Language Models: The Future of Explainable Operations Research
Prune and Tune: Improving Efficient Pruning Techniques for Massive Language Models
Unlocking Point Processes through Point Set Diffusion
Mogrifier LSTM
Learning Deep Models: Critical Points and Local Openness
GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets
Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback
On the Universality of the Double Descent Peak in Ridgeless Regression
Image Inpainting via Iteratively Decoupled Probabilistic Modeling
Towards Metamerism via Foveated Style Transfer
Training language models to summarize narratives improves brain alignment
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model
InstantSplamp: Fast and Generalizable Stenography Framework for Generative Gaussian Splatting
Learning Deep Features in Instrumental Variable Regression
MamKO: Mamba-based Koopman operator for modeling and predictive control
DittoGym: Learning to Control Soft Shape-Shifting Robots
Perceiver IO: A General Architecture for Structured Inputs & Outputs
Consistency Regularization for Generative Adversarial Networks
Causal Discovery with Reinforcement Learning
Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction
Order-Preserving GFlowNets
MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
fairret: a Framework for Differentiable Fairness Regularization Terms
The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning
Scaling Laws For Deep Learning Based Image Reconstruction
THOMAS: Trajectory Heatmap Output with learned Multi-Agent Sampling
Replay across Experiments: A Natural Extension of Off-Policy RL
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework
The Modality Focusing Hypothesis: Towards Understanding Crossmodal Knowledge Distillation
Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality
CL-MFAP: A Contrastive Learning-Based Multimodal Foundation Model for Molecular Property Prediction and Antibiotic Screening
Zero-shot Synthesis with Group-Supervised Learning
Span Recovery for Deep Neural Networks with Applications to Input Obfuscation
A Simple yet Effective ΔΔG Predictor is An Unsupervised Antibody Optimizer and Explainer
Estimating the Probabilities of Rare Outputs in Language Models
ASID: Active Exploration for System Identification in Robotic Manipulation
Deep Orientation Uncertainty Learning based on a Bingham Loss
Incremental Network Quantization: Towards Lossless CNNs with Low-precision Weights
Diversity and Depth in Per-Example Routing Models
InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma
Exploration in Reinforcement Learning with Deep Covering Options
Idempotent Generative Network
De novo Protein Design Using Geometric Vector Field Networks
Do Vision & Language Decoders use Images and Text equally? How Self-consistent are their Explanations?
Controlled LLM Decoding via Discrete Auto-regressive Biasing
Improved Techniques for Optimization-Based Jailbreaking on Large Language Models
eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels
Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization
SWEb: A Large Web Dataset for the Scandinavian Languages
Offline RL in Regular Decision Processes: Sample Efficiency via Language Metrics
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning
Empowering LLM Agents with Zero-Shot Optimal Decision-Making through Q-learning
Gradient $\ell_1$ Regularization for Quantization Robustness
Characteristic Neural Ordinary Differential Equation
Taming Overconfidence in LLMs: Reward Calibration in RLHF
NeurQuRI: Neural Question Requirement Inspector for Answerability Prediction in Machine Reading Comprehension
On the hardness of learning under symmetries
Group Ligands Docking to Protein Pockets
Neural Parameter Allocation Search
Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams
Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning
Adaptive Transformer Programs: Bridging the Gap Between Performance and Interpretability in Transformers
Dialogue Learning With Human-in-the-Loop
Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
Uncertainty modeling for fine-tuned implicit functions
Expressive Monotonic Neural Networks
PICASO: Permutation-Invariant Context Composition with State Space Models
Higher-Order Function Networks for Learning Composable 3D Object Representations
Learning transferable motor skills with hierarchical latent mixture policies
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
No Location Left Behind: Measuring and Improving the Fairness of Implicit Representations for Earth Data
Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders
Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching
Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation
Deep Reinforcement Learning for Cost-Effective Medical Diagnosis
Neumann Optimizer: A Practical Optimization Algorithm for Deep Neural Networks
Low-dimensional statistical manifold embedding of directed graphs
Real2Code: Reconstruct Articulated Objects via Code Generation
Deep Neural Network Initialization with Sparsity Inducing activations
Population Transformer: Learning Population-level Representations of Neural Activity
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design
FasterSeg: Searching for Faster Real-time Semantic Segmentation
Mapping the Typographic Latent Space of Digits
Stein Latent Optimization for Generative Adversarial Networks
From Attention to Activation: Unraveling the Enigmas of Large Language Models
Robustness of Quantum Algorithms for Nonconvex Optimization
Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text
Directed-Info GAIL: Learning Hierarchical Policies from Unsegmented Demonstrations using Directed Information
Improved Learning-augmented Algorithms for k-means and k-medians Clustering
Large Language Models as Generalizable Policies for Embodied Tasks
DexTrack: Towards Generalizable Neural Tracking Control for Dexterous Manipulation from Human References
Transformer-VQ: Linear-Time Transformers via Vector Quantization
Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning
Understanding intermediate layers using linear classifier probes
An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality
Learning to Jointly Share and Prune Weights for Grounding Based Vision and Language Models
Multi-task Learning with 3D-Aware Regularization
GraphRouter: A Graph-based Router for LLM Selections
Local Graph Clustering with Noisy Labels
Adapt-∞: Scalable Continual Multimodal Instruction Tuning via Dynamic Data Selection
Evaluating Long-Term Memory in 3D Mazes
Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks
Inverse Attention Agents for Multi-Agent Systems
Dual-Encoders for Extreme Multi-label Classification
Continual Transformers: Redundancy-Free Attention for Online Inference
MetaNorm: Learning to Normalize Few-Shot Batches Across Domains
Taking Notes on the Fly Helps Language Pre-Training
Retrieval-Augmented Generation for Code Summarization via Hybrid GNN
HMoRA: Making LLMs More Effective with Hierarchical Mixture of LoRA Experts
Revisit the Open Nature of Open Vocabulary Semantic Segmentation
Self-supervision through Random Segments with Autoregressive Coding (RandSAC)
Dynamic Time Lag Regression: Predicting What & When
Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation
SALD: Sign Agnostic Learning with Derivatives
Unsupervised Feature Learning for Audio Analysis
Masks, Signs, And Learning Rate Rewinding
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control
On the Transfer of Object-Centric Representation Learning
Multi-Stage Episodic Control for Strategic Exploration in Text Games
Intriguing Properties of Adversarial Training at Scale
Fusion Is Not Enough: Single Modal Attacks on Fusion Models for 3D Object Detection
Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
MoDGS: Dynamic Gaussian Splatting from Casually-captured Monocular Videos with Depth Priors
Space Group Constrained Crystal Generation
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
Cross-Attentional Audio-Visual Fusion for Weakly-Supervised Action Localization
Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram
A Sublinear Adversarial Training Algorithm
Concept Gradient: Concept-based Interpretation Without Linear Assumption
Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent
Task Planning for Visual Room Rearrangement under Partial Observability
Octavius: Mitigating Task Interference in MLLMs via LoRA-MoE
Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift
Self-Supervised Set Representation Learning for Unsupervised Meta-Learning
Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time
The Semantic Hub Hypothesis: Language Models Share Semantic Representations Across Languages and Modalities
Identifying and Controlling Important Neurons in Neural Machine Translation
Deep Linear Probe Generators for Weight Space Learning
Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs
Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks
Robust NAS under adversarial training: benchmark, theory, and beyond
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
Spreading vectors for similarity search
Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery
DyRep: Learning Representations over Dynamic Graphs
EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision
Automated curriculum generation through setter-solver interactions
Epistemic Monte Carlo Tree Search
Open-Vocabulary Object Detection upon Frozen Vision and Language Models
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples
Geometric and Physical Quantities improve E(3) Equivariant Message Passing
Distilled Self-Critique of LLMs with Synthetic Data: a Bayesian Perspective
One Transformer Can Understand Both 2D & 3D Molecular Data
Mitigating Memorization in Language Models
Chemistry-Inspired Diffusion with Non-Differentiable Guidance
Scaling Diffusion Language Models via Adaptation from Autoregressive Models
LaGeM: A Large Geometry Model for 3D Representation Learning and Diffusion
PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation
Cut Your Losses in Large-Vocabulary Language Models
Circumventing Concept Erasure Methods For Text-To-Image Generative Models
Efficient Residual Learning with Mixture-of-Experts for Universal Dexterous Grasping
Discovering Temporally-Aware Reinforcement Learning Algorithms
ALLaM: Large Language Models for Arabic and English
Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures
PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics
Point Cloud GAN
Generative Monoculture in Large Language Models
Learning Sparse Group Models Through Boolean Relaxation
Understanding Why Generalized Reweighting Does Not Improve Over ERM
Repetition Improves Language Model Embeddings
On Computation and Generalization of Generative Adversarial Imitation Learning
Universal Transformers
Neural Active Learning Beyond Bandits
TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
DOP: Off-Policy Multi-Agent Decomposed Policy Gradients
Inequality phenomenon in l ∞ -adversarial training, and its unrealized threats
PoNet: Pooling Network for Efficient Token Mixing in Long Sequences
Diffusion Transformers for Tabular Data Time Series Generation
Comparing Distributions by Measuring Differences that Affect Decision Making
Improved Adversarial Image Captioning
MGCFNN: A Neural MultiGrid Solver with Novel Fourier Neural Network for High Wave Number Helmholtz Equations
OmniRe: Omni Urban Scene Reconstruction
Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition
Action abstractions for amortized sampling
Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts
Learning "What-if" Explanations for Sequential Decision-Making
Delving into Transferable Adversarial Examples and Black-box Attacks
Lemur: Integrating Large Language Models in Automated Program Verification
Generalization of Scaled Deep ResNets in the Mean-Field Regime
Variance Reduction for Reinforcement Learning in Input-Driven Environments
Bisimulation Metric for Model Predictive Control
Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL
CAS: A Probability-Based Approach for Universal Condition Alignment Score
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
Neural Program Synthesis with Query
nGPT: Normalized Transformer with Representation Learning on the Hypersphere
Unsupervised Audiovisual Synthesis via Exemplar Autoencoders
CaPC Learning: Confidential and Private Collaborative Learning
In vivo cell-type and brain region classification via multimodal contrastive learning
Generalizing Hamiltonian Monte Carlo with Neural Networks
Combinatorial-Probabilistic Trade-Off: P-Values of Community Properties Test in the Stochastic Block Models
FRESCO: Federated Reinforcement Energy System for Cooperative Optimization
Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models
Surgical, Cheap, and Flexible: Mitigating False Refusal in Language Models via Single Vector Ablation
Benefits of Depth for Long-Term Memory of Recurrent Networks
Target-Side Input Augmentation for Sequence to Sequence Generation
Motion Guidance: Diffusion-Based Image Editing with Differentiable Motion Estimators
End-to-End (Instance)-Image Goal Navigation through Correspondence as an Emergent Phenomenon
Does Deep Learning Learn to Abstract? A Systematic Probing Framework
Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks
3D-Properties: Identifying Challenges in DPO and Charting a Path Forward
Whole-Song Hierarchical Generation of Symbolic Music Using Cascaded Diffusion Models
Training Graph Transformers via Curriculum-Enhanced Attention Distillation
MMA Training: Direct Input Space Margin Maximization through Adversarial Training
Deep Learning on Implicit Neural Representations of Shapes
Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
Conditional Networks for Few-Shot Semantic Segmentation
HiViT: A Simpler and More Efficient Design of Hierarchical Vision Transformer
Learning Human-Compatible Representations for Case-Based Decision Support
Optimal Learning of Kernel Logistic Regression for Complex Classification Scenarios
MLP-Attention: Improving Transformer Architecture with MLP Attention Weights
SoftZoo: A Soft Robot Co-design Benchmark For Locomotion In Diverse Environments
PFGuard: A Generative Framework with Privacy and Fairness Safeguards
A Change of Heart: Improving Speech Emotion Recognition through Speech-to-Text Modality Conversion
Score-based Self-supervised MRI Denoising
Variational Information Pursuit for Interpretable Predictions
Uni3D: Exploring Unified 3D Representation at Scale
Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization
Inductive Bias of Deep Convolutional Networks through Pooling Geometry
Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts
ConvCodeWorld: Benchmarking Conversational Code Generation in Reproducible Feedback Environments
Scaling Transformers for Low-Bitrate High-Quality Speech Coding
Unsupervised Learning via Meta-Learning
Single Teacher, Multiple Perspectives: Teacher Knowledge Augmentation for Enhanced Knowledge Distillation
Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning
The Preimage of Rectifier Network Activities
Simple Augmentation Goes a Long Way: ADRL for DNN Quantization
On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters
Self-Supervised Learning of Appliance Usage
Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values
Visual hyperacuity with moving sensor and recurrent neural computations
Measuring Vision-Language STEM Skills of Neural Models
Computational Explorations of Total Variation Distance
Dynamic Diffusion Transformer
Emergent Communication in a Multi-Modal, Multi-Step Referential Game
Training GANs with Optimism
Pruned Graph Scattering Transforms
Do LLMs estimate uncertainty well in instruction-following?
Continual Slow-and-Fast Adaptation of Latent Neural Dynamics (CoSFan): Meta-Learning What-How & When to Adapt
Let Models Speak Ciphers: Multiagent Debate through Embeddings