yusuke1997/dblp-id-title huggingface dataset:
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks
Sampling with Mollified Interaction Energy Descent
Episodic Curiosity through Reachability
A Unified Algebraic Perspective on Lipschitz Neural Networks
Overcoming the Disentanglement vs Reconstruction Trade-off via Jacobian Supervision
Brusleattack: a Query-Efficient Score- based Black-Box Sparse Adversarial Attack
TopoGaussian: Inferring Internal Topology Structures from Visual Clues
Learning system dynamics without forgetting
Martingale Posterior Neural Processes
On Adversarial Training without Perturbing all Examples
Fairness in Representation for Multilingual NLP: Insights from Controlled Experiments on Conditional Language Modeling
PaLD: Detection of Text Partially Written by Large Language Models
Variational Bayesian Pseudo-Coreset
Bayes Risk CTC: Controllable CTC Alignment in Sequence-to-Sequence Tasks
Learning Space Partitions for Nearest Neighbor Search
Measuring And Improving Engagement of Text-to-Image Generation Models
Entropic gradient descent algorithms and wide flat minima
ACTIVE: Offline Reinforcement Learning via Adaptive Imitation and In-sample V-Ensemble
Meta Back-Translation
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
DELIFT: Data Efficient Language model Instruction Fine-Tuning
On Statistical Bias In Active Learning: How and When to Fix It
Revamp: Automated Simulations of Adversarial Attacks on Arbitrary Objects in Realistic Scenes
Scaling Speech-Text Pre-training with Synthetic Interleaved Data
Fooling Detection Alone is Not Enough: Adversarial Attack against Multiple Object Tracking
Scalable Bayesian Learning with posteriors
Shuffle Private Stochastic Convex Optimization
Eva: Practical Second-order Optimization with Kronecker-vectorized Approximation
Neural Fourier Transform: A General Approach to Equivariant Representation Learning
Win: Weight-Decay-Integrated Nesterov Acceleration for Adaptive Gradient Algorithms
Sequential Learning of Neural Networks for Prequential MDL
Unsupervised Learning of the Set of Local Maxima
MELODI: Exploring Memory Compression for Long Contexts
Online Information Acquisition: Hiring Multiple Agents
Efficient and Trustworthy Causal Discovery with Latent Variables and Complex Relations
Recursive Generalization Transformer for Image Super-Resolution
Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data
Diff-PIC: Revolutionizing Particle-In-Cell Nuclear Fusion Simulation with Diffusion Models
Leveraging Importance Weights in Subset Selection
High Fidelity Speech Synthesis with Adversarial Networks
Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models
Benchmarking Agentic Workflow Generation
Improving Zero-Shot Voice Style Transfer via Disentangled Representation Learning
One Forward is Enough for Neural Network Training via Likelihood Ratio Method
Scalable Subset Sampling with Neural Conditional Poisson Networks
Shake-Shake regularization of 3-branch residual networks
Relaxed Quantization for Discretized Neural Networks
The Lie Derivative for Measuring Learned Equivariance
Learning Continuous Environment Fields via Implicit Functions
Fully Unsupervised Diversity Denoising with Convolutional Variational Autoencoders
Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations
Learning with Mixture of Prototypes for Out-of-Distribution Detection
BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries
An Empirical Analysis of Uncertainty in Large Language Model Evaluations
Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models
Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization
PRIME: Prioritizing Interpretability in Failure Mode Extraction
The Expressive Power of Low-Rank Adaptation
Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences
Robust LLM safeguarding via refusal feature adversarial training
Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants
Deep learning mutation prediction enables early stage lung cancer detection in liquid biopsy
DARA: Dynamics-Aware Reward Augmentation in Offline Reinforcement Learning
FedPara: Low-rank Hadamard Product for Communication-Efficient Federated Learning
Medium-Difficulty Samples Constitute Smoothed Decision Boundary for Knowledge Distillation on Pruned Datasets
Cross-Domain Off-Policy Evaluation and Learning for Contextual Bandits
Towards Fairness constrained Restless Multi-Armed Bandits: a Case Study of Maternal and child Care Domain
Decoupling Representation and Classifier for Long-Tailed Recognition
Unsupervised 3D Object Learning through Neuron Activity aware Plasticity
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization
Paraphrase Loss for Abstractive Summarization
Locality Sensitive Sparse Encoding for Learning World Models Online
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap
Learning perturbation sets for robust machine learning
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
Efficient Neural Causal Discovery without Acyclicity Constraints
Handling Delay in Real-Time Reinforcement Learning
ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text
CirT: Global Subseasonal-to-Seasonal Forecasting with Geometry-inspired Transformer
What Are Good Positional Encodings for Directed Graphs?
Self-Supervised Speech Quality Estimation and Enhancement Using Only Clean Speech
Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies
SpectralNet: Spectral Clustering using Deep Neural Networks
UniDetox: Universal Detoxification of Large Language Models via Dataset Distillation
Model Risk-sensitive Offline Reinforcement Learning
CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech
Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX
SCHEMA: State CHangEs MAtter for Procedure Planning in Instructional Videos
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization
Selective Ensembles for Consistent Predictions
Snip: single-Shot Network Pruning based on Connection sensitivity
Learning to Sample with Local and Global Contexts in Experience Replay Buffer
ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks
The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers
A RAD approach to deep mixture models
CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Objects
Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model
AgentSquare: Automatic LLM Agent Search in Modular Design Space
Provable Filter Pruning for Efficient Neural Networks
Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design
Extendable and Iterative Structure Learning Strategy for Bayesian Networks
MediConfusion: Can you trust your AI radiologist? Probing the reliability of multimodal medical foundation models
Where We Have Arrived in Proving the Emergence of Sparse Interaction Primitives in DNNs
Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
TranSpeech: Speech-to-Speech Translation With Bilateral Perturbation
Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks
Decoupling Angles and Strength in Low-rank Adaptation
Faster Cascades via Speculative Decoding
Towards Principled Evaluations of Sparse Autoencoders for Interpretability and Control
Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games
Beyond Words: A Topological Exploration of Coherence in Text Documents
Frequency-based Search-control in Dyna
Making Retrieval-Augmented Language Models Robust to Irrelevant Context
DPSNet: End-to-end Deep Plane Sweep Stereo
Bayesian-Driven Learning of A New Weighted Tensor Norm for Tensor Recovery
One-hot Generalized Linear Model for Switching Brain State Discovery
Behavior Proximal Policy Optimization
Multimodal Situational Safety
Measuring Compositional Generalization: A Comprehensive Method on Realistic Data
Self-supervised Monocular Depth Estimation Robust to Reflective Surface Leveraged by Triplet Mining
Usable Information and Evolution of Optimal Representations During Training
Learning to Describe Scenes with Programs
Contrastive Corpus Attribution for Explaining Representations
Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds
SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing
ReNovo: Retrieval-Based \emph{De Novo} Mass Spectrometry Peptide Sequencing
NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization
Neural DAG Scheduling via One-Shot Priority Sampling
TopEx: Topic-based Explanations for Model Comparison
SVQN: Sequential Variational Soft Q-Learning Networks
Lumina-T2X: Scalable Flow-based Large Diffusion Transformer for Flexible Resolution Generation
Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
Disentangling 3D Animal Pose Dynamics with Scrubbed Conditional Latent Variables
Learning Rationalizable Equilibria in Multiplayer Games
Diverse Video Generation using a Gaussian Process Trigger
L2 Norm Guided Adaptive Computation
Stochastic Multi-Person 3D Motion Forecasting
Injective flows for star-like manifolds
HiBug2: Efficient and Interpretable Error Slice Discovery for Comprehensive Model Debugging
Discrete Contrastive Diffusion for Cross-Modal Music and Image Generation
A comprehensive, application-oriented study of catastrophic forgetting in DNNs
CAQL: Continuous Action Q-Learning
Improving Neural Network Accuracy by Concurrently Training with a Twin Network
Few-Shot Domain Adaptation For End-to-End Communication
Fusing Models with Complementary Expertise
Ground-A-Video: Zero-shot Grounded Video Editing using Text-to-image Diffusion Models
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
Supervision Complexity and its Role in Knowledge Distillation
Composing Ensembles of Pre-trained Models via Iterative Consensus
Local Search GFlowNets
Training binary neural networks with real-to-binary convolutions
Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering
Nesterov acceleration in benignly non-convex landscapes
Improving Generalization in Meta Reinforcement Learning using Learned Objectives
A Constructive Prediction of the Generalization Error Across Scales
Robust Reinforcement Learning for Autonomous Driving
TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoning
IFR-Explore: Learning Inter-object Functional Relationships in 3D Indoor Scenes
Variational Search Distributions
GI-GS: Global Illumination Decomposition on Gaussian Splatting for Inverse Rendering
Missingness Bias in Model Debugging
World Model on Million-Length Video And Language With Blockwise RingAttention
Graph Neural Networks Can (Often) Count Substructures
Tiny Attention: A Simple yet Effective Method for Learning Contextual Word Embeddings
InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization
Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models
Denoising Task Difficulty-based Curriculum for Training Diffusion Models
Narrowing Information Bottleneck Theory for Multimodal Image-Text Representations Interpretability
Conversational Drug Editing Using Retrieval and Domain Feedback
PharmacoMatch: Efficient 3D Pharmacophore Screening via Neural Subgraph Matching
Causally Motivated Sycophancy Mitigation for Large Language Models
IamNN: Iterative and Adaptive Mobile Neural Network for efficient image classification
TAU-106K: A New Dataset for Comprehensive Understanding of Traffic Accident
Learning to Contextualize Web Pages for Enhanced Decision Making by LLM Agents
OWL: A Large Language Model for IT Operations
Growing Efficient Deep Networks by Structured Continuous Sparsification
CTSyn: A Foundation Model for Cross Tabular Data Generation
Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation
PiCO: Contrastive Label Disambiguation for Partial Label Learning
Rethinking Reward Model Evaluation: Are We Barking up the Wrong Tree?
Enhancing Compositional Text-to-Image Generation with Reliable Random Seeds
CogCoM: A Visual Language Model with Chain-of-Manipulations Reasoning
Select before Act: Spatially Decoupled Action Repetition for Continuous Control
Message-passing Selection: Towards Interpretable GNNs for Graph Classification
Pseudo Labels for Single Positive Multi-Label Learning
DeepSPF: Spherical SO(3)-Equivariant Patches for Scan-to-CAD Estimation
Linear Representations of Political Perspective Emerge in Large Language Models
A Theory for Token-Level Harmonization in Retrieval-Augmented Generation
Dissecting learning and forgetting in language model finetuning
Scalable Private Learning with PATE
MOFI: Learning Image Representations from Noisy Entity Annotated Images
A Framework for Policy Evaluation Enhancement by Diffusion Models
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing
Learning Long Range Dependencies on Graphs via Random Walks
PanoDiffusion: 360-degree Panorama Outpainting via Diffusion
GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries
Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM
$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
Wasserstein-Regularized Conformal Prediction under General Distribution Shift
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
Towards Robust Multimodal Open-set Test-time Adaptation via Adaptive Entropy-aware Optimization
Learning Interleaved Image-Text Comprehension in Vision-Language Large Models
Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR and Worst Path
AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark
On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation
Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction
Transferable Adversarial Attack based on Integrated Gradients
Beyond Imitation: Leveraging Fine-grained Quality Signals for Alignment
A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learning
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
Averager Student: Distillation from Undistillable Teacher
Toward Learning Latent-Variable Representations of Microstructures by Optimizing in Spatial Statistics Space
6DGS: Enhanced Direction-Aware Gaussian Splatting for Volumetric Rendering
Online Facility Location with Predictions
Strategic Classification with Graph Neural Networks
Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs
A differentiable brain simulator bridging brain simulation and brain-inspired computing
5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings
Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation
Social-Transmotion: Promptable Human Trajectory Prediction
Learning Structural Edits via Incremental Tree Transformations
Agent-Oriented Planning in Multi-Agent Systems
CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation
Automated Mapping of Healthcare Concepts to a Standardized Healthcare Taxonomy
PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization
Data Shapley in One Training Run
Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems
PF-LRM: Pose-Free Large Reconstruction Model for Joint Pose and Shape Prediction
Extreme Q-Learning: MaxEnt RL without Entropy
OSTQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
TEMPERA: Test-Time Prompt Editing via Reinforcement Learning
WildChat: 1M ChatGPT Interaction Logs in the Wild
Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited
AdvPaint: Protecting Images from Inpainting Manipulation via Adversarial Attention Disruption
Fast Generic Interaction Detection for Model Interpretability and Compression
Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality
Self-Improvement in Language Models: The Sharpening Mechanism
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
Holistically Evaluating the Environmental Impact of Creating Language Models
Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs
CoMRes: Semi-Supervised Time Series Forecasting Utilizing Consensus Promotion of Multi-Resolution
Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
PT-T2I/V: An Efficient Proxy-Tokenized Diffusion Transformer for Text-to-Image/Video-Task
Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming
Time-Dependent Representation for Neural Event Sequence Prediction
Multi-agent query reformulation: Challenges and the role of diversity
Transformer protein language models are unsupervised structure learners
Efficiently testing local optimality and escaping saddles for ReLU networks
Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy
UniMax: Fairer and More Effective Language Sampling for Large-Scale Multilingual Pretraining
LPT: Long-tailed Prompt Tuning for Image Classification
Looking into User's Long-term Interests through the Lens of Conservative Evidential Learning
The Implicit Bias of Depth: How Incremental Learning Drives Generalization
A representation-learning game for classes of prediction tasks
GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning
HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark
Towards Robust Neural Networks via Close-loop Control
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
Environment Probing Interaction Policies
Denoising Diffusion Step-aware Models
On Hyperparameter Optimization in Learning Systems
Spiking Vision Transformer with Saccadic Attention
CARTS: Advancing Neural Theorem Proving with Diversified Tactic Calibration and Bias-Resistant Tree Search
Learning Successor Features with Distributed Hebbian Temporal Memory
SyllableLM: Learning Coarse Semantic Units for Speech Language Models
Sparse Attention with Learning to Hash
Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators
Towards Learning High-Precision Least Squares Algorithms with Sequence Models
Self-Evolved Reward Learning for LLMS
SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning
Integer Networks for Data Compression with Latent-Variable Models
Improving Generalization of Alignment with Human Preferences through Group Invariant Learning
Variational Best-of-N Alignment
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
The Tilted Variational Autoencoder: Improving Out-of-Distribution Detection
Tool-Augmented Reward Modeling
Quantifying Memorization Across Neural Language Models
ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity
Neural Image-based Avatars: Generalizable Radiance Fields for Human Avatar Modeling
Estimating Lipschitz constants of monotone deep equilibrium models
MoE++: Accelerating Mixture-of-Experts Methods with Zero-Computation Experts
Spatially Transformed Adversarial Examples
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds
Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning
Lookahead: A Far-sighted Alternative of Magnitude-based Pruning
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
Correlative Information Maximization Based Biologically Plausible Neural Networks for Correlated Source Separation
CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation
Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning
Explaining RL Decisions with Trajectories
Compressive Transformers for Long-Range Sequence Modelling
Do Contemporary Causal Inference Models Capture Real-World Heterogeneity? Findings from a Large-Scale Benchmark
RODE: Learning Roles to Decompose Multi-Agent Tasks
Symbolic Regression in Financial Economics
SNOW: Subscribing to Knowledge via Channel Pooling for Transfer & Lifelong Learning of Convolutional Neural Networks
Effective pruning of web-scale datasets based on complexity of concept clusters
metabench - A Sparse Benchmark of Reasoning and Knowledge in Large Language Models
Modeling Future Conversation Turns to Teach LLMs to Ask Clarifying Questions
Denevil: towards Deciphering and Navigating the Ethical Values of Large Language Models via Instruction Learning
When is RL better than DPO in RLHF? A Representation and Optimization Perspective
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
Execution-guided within-prompt search for programming-by-example
DDPNOpt: Differential Dynamic Programming Neural Optimizer
Diffusion-NPO: Negative Preference Optimization for Better Preference Aligned Generation of Diffusion Models
On The Specialization of Neural Modules
Massive Editing for Large Language Models via Meta Learning
The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws
BEND: Benchmarking DNA Language Models on Biologically Meaningful Tasks
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data
Bayesian Treatment of the Spectrum of the Empirical Kernel in (Sub)Linear-Width Neural Networks
TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data
The importance of feature preprocessing for differentially private linear optimization
Understanding and Leveraging Overparameterization in Recursive Value Estimation
Block and Subword-Scaling Floating-Point (BSFP) : An Efficient Non-Uniform Quantization For Low Precision Inference
Selective induction Heads: How Transformers Select Causal Structures in Context
Accelerating Inference of Retrieval-Augmented Generation via Sparse Context Selection
Pre-training Molecular Graph Representation with 3D Geometry
AlignFlow: Learning from multiple domains via normalizing flows
Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems
Softened Symbol Grounding for Neuro-symbolic Systems
Attention with Markov: A Curious Case of Single-layer Transformers
Efficient Learning with Sine-Activated Low-Rank Matrices
Guarded Policy Optimization with Imperfect Online Demonstrations
Incremental Learning of Structured Memory via Closed-Loop Transcription
Audio Lottery: Speech Recognition Made Ultra-Lightweight, Noise-Robust, and Transferable
STBLLM: Breaking the 1-Bit Barrier with Structured Binary LLMs
Generalized Tensor Models for Recurrent Neural Networks
Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation
New Bounds For Distributed Mean Estimation and Variance Reduction
FedExP: Speeding Up Federated Averaging via Extrapolation
Forget the Data and Fine-Tuning! Just Fold the Network to Compress