yusuke1997/dblp-id-title huggingface dataset:
PuzzleFusion++: Auto-agglomerative 3D Fracture Assembly by Denoise and Verify
That Label's got Style: Handling Label Style Bias for Uncertain Image Segmentation
Self-supervised Visual Reinforcement Learning with Object-centric Representations
Learning to Map for Active Semantic Goal Navigation
Lambda-Skip Connections: the architectural component that prevents Rank Collapse
Optimal Regularization can Mitigate Double Descent
MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI
Bidirectional Temporal Diffusion Model for Temporally Consistent Human Animation
Metric Transform: Exploring beyond Affine Transform for Neural Networks
CR-CTC: Consistency regularization on CTC for improved speech recognition
Neural Map: Structured Memory for Deep Reinforcement Learning
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization
Generalization in data-driven models of primary visual cortex
Exploring Dimensional Collapse in Self-Supervised Video Representation Learning
Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do
CIFAR-10-Warehouse: Broad and More Realistic Testbeds in Model Generalization Analysis
On the Robustness of Safe Reinforcement Learning under Observational Perturbations
The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry
RTFS-Net: Recurrent Time-Frequency Modelling for Efficient Audio-Visual Speech Separation
BOIL: Towards Representation Change for Few-shot Learning
AutoLoss: Learning Discrete Schedule for Alternate Optimization
Understanding and Adopting Rational Behavior by Bellman Score Estimation
PhyloLM: Inferring the Phylogeny of Large Language Models and Predicting their Performances in Benchmarks
Don't Take Things Out of Context: Attention Intervention for Enhancing Chain-of-Thought Reasoning in Large Language Models
Efficient Heterogeneous Meta-Learning via Channel Shuffling Modulation
Action-dependent Control Variates for Policy Optimization via Stein Identity
Differentiable Reasoning over a Virtual Knowledge Base
UniAdapter: Unified Parameter-Efficient Transfer Learning for Cross-modal Modeling
Decompositional Generation Process for Instance-Dependent Partial Label Learning
When Prompt Engineering Meets Software Engineering: CNL-P as Natural and Robust "APIs" for Human-AI Interaction
EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation
Spatio-Temporal Few-Shot Learning via Diffusive Neural Network Generation
switch-GLAT: Multilingual Parallel Machine Translation Via Code-Switch Decoder
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?
Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning
On Improving the Numerical Stability of Winograd Convolutions
A Common Pitfall of Margin-based Language Model Alignment: Gradient Entanglement
Learning Symbolic Models for Graph-structured Physical Mechanism
Learning deep graph matching with channel-independent embedding and Hungarian attention
Scalable and Certifiable Graph Unlearning: Overcoming the Approximation Error Barrier
Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS
Mode Regularized Generative Adversarial Networks
Generalization through Memorization: Nearest Neighbor Language Models
Stabilizing Backpropagation Through Time to Learn Complex Physics
Semantic Patch Embedding for Security Detection: A Fine-to-Coarse Grained Approach
Mitigating Modality Prior-Induced Hallucinations in Multimodal Large Language Models via Deciphering Attention Causality
Image2Sentence based Asymmetrical Zero-shot Composed Image Retrieval
Post hoc Explanations may be Ineffective for Detecting Unknown Spurious Correlation
CoordX: Accelerating Implicit Neural Representation with a Split MLP Architecture
Implicit In-context Learning
Neural Systematic Binder
Multi-View Data Generation Without View Supervision
A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics
LongWriter: Unleashing 10, 000+ Word Generation from Long Context LLMs
Robust Classification via Regression for Learning with Noisy Labels
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses
Generative networks as inverse problems with Scattering transforms
RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code
RuAG: Learned-rule-augmented Generation for Large Language Models
MGMapNet: Multi-Granularity Representation Learning for End-to-End Vectorized HD Map Construction
AlpaGasus: Training a Better Alpaca with Fewer Data
Spectral Normalization for Generative Adversarial Networks
OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling
Mapping conditional distributions for domain adaptation under generalized target shift
Min-K%++: Improved Baseline for Pre-Training Data Detection from Large Language Models
Hard-Meta-Dataset++: Towards Understanding Few-Shot Performance on Difficult Tasks
Objects in Semantic Topology
Towards a statistical theory of data selection under weak supervision
Adaptive Input Representations for Neural Language Modeling
Deep Temporal Graph Clustering
RocketEval: Efficient automated LLM evaluation via grading checklist
Graph Domain Adaptation via Theory-Grounded Spectral Regularization
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
Variational Inference for SDEs Driven by Fractional Noise
Conditional Information Bottleneck Approach for Time Series Imputation
Efficient ConvBN Blocks for Transfer Learning and Beyond
On Designing General and Expressive Quantum Graph Neural Networks with Applications to MILP Instance Representation
Bias Correction of Learned Generative Models via Likelihood-free Importance Weighting
OPTQ: Accurate Quantization for Generative Pre-trained Transformers
CONTRA: Conformal Prediction Region via Normalizing Flow Transformation
Rationalizing and Augmenting Dynamic Graph Neural Networks
Robust Curriculum Learning: from clean label detection to noisy label self-correction
Grounding Multimodal Large Language Models to the World
DiffusionSat: A Generative Foundation Model for Satellite Imagery
Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning
CodeBPE: Investigating Subtokenization Options for Large Language Model Pretraining on Source Code
Meta-Learning in Games
PaPaGei: Open Foundation Models for Optical Physiological Signals
Characterizing intrinsic compositionality in transformers with Tree Projections
Efficient Conditionally Invariant Representation Learning
Memorization Capacity of Neural Networks with Conditional Computation
General Stability Analysis for Zeroth-Order Optimization Algorithms
Logic-guided Deep Reinforcement Learning for Stock Trading
On Speeding Up Language Model Evaluation
FedMix: Approximation of Mixup under Mean Augmented Federated Learning
Counterfactual Plans under Distributional Ambiguity
Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
GIO: Gradient Information Optimization for Training Dataset Selection
ILA-DA: Improving Transferability of Intermediate Level Attack with Data Augmentation
Expressive Power of Invariant and Equivariant Graph Neural Networks
Sequential Controlled Langevin Diffusions
Understanding Domain Randomization for Sim-to-real Transfer
AutoGT: Automated Graph Transformer Architecture Search
Is ImageNet worth 1 video? Learning strong image encoders from 1 long unlabelled video
On the Equivalence between Positional Node Embeddings and Structural Graph Representations
General Purpose Artificial Intelligence Systems as Group Agents
ActionReasoningBench: Reasoning about Actions with and without Ramification Constraints
Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF
On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning
Sparse Autoencoders Do Not Find Canonical Units of Analysis
Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning
From Zero to Turbulence: Generative Modeling for 3D Flow Simulation
Rational Decision-Making Agent with Learning Internal Utility Judgment
Individually Fair Gradient Boosting
ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities
Mathematical Reasoning via Self-supervised Skip-tree Training
What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models
Generative Ratio Matching Networks
Kill Two Birds with One Stone: Rethinking Data Augmentation for Deep Long-tailed Learning
Pseudoinverse-Guided Diffusion Models for Inverse Problems
Training One-Dimensional Graph Neural Networks is NP-Hard
Property Controllable Variational Autoencoder via Invertible Mutual Dependence
Uncovering Gaps in How Humans and LLMs Interpret Subjective Language
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory
Not All LLM-Generated Data Are Equal: Rethinking Data Weighting in Text Classification
Improving Neural Language Models with a Continuous Cache
Information Theoretic Text-to-Image Alignment
Equivariant Matrix Function Neural Networks
MeToken: Uniform Micro-environment Token Boosts Post-Translational Modification Prediction
Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization
Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions
Large scale distributed neural network training through online distillation
Symmetry-Breaking Convergence Analysis of Certain Two-layered Neural Networks with ReLU nonlinearity
Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning
Learning Neural Event Functions for Ordinary Differential Equations
Learning-Based Frequency Estimation Algorithms
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning
ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion
Score-Based Generative Modeling through Stochastic Differential Equations
Monotonic Chunkwise Attention
An Exponential Learning Rate Schedule for Deep Learning
SEA: Sparse Linear Attention with Estimated Attention Mask
Revisiting In-context Learning Inference Circuit in Large Language Models
Heredity-aware Child Face Image Generation with Latent Space Disentanglement
Second-Order Min-Max Optimization with Lazy Hessians
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN
Performance Bounds for Model and Policy Transfer in Hidden-parameter MDPs
Online Clustering with Nearly Optimal Consistency
Initialization and Regularization of Factorized Neural Layers
Sparse Random Networks for Communication-Efficient Federated Learning
EvA: Erasing Spurious Correlations with Activations
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation
Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuning
Deep Rewiring: Training very sparse deep networks
On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning
Adapting to Reward Progressivity via Spectral Reinforcement Learning
PeFLL: Personalized Federated Learning by Learning to Learn
Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL
Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach
Verifying the Union of Manifolds Hypothesis for Image Data
Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond
LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
Loss-aware Weight Quantization of Deep Networks
Long-Short Decision Transformer: Bridging Global and Local Dependencies for Generalized Decision-Making
A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error
Learning Temporally Causal Latent Processes from General Temporal Data
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology
Graph Transformers on EHRs: Better Representation Improves Downstream Performance
Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows
How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections
Score Models for Offline Goal-Conditioned Reinforcement Learning
Rethinking Model Ensemble in Transfer-based Adversarial Attacks
Last Iterate Convergence of Incremental Methods as a Model of Forgetting
Auto-Transfer: Learning to Route Transferable Representations
Progressive Mixed-Precision Decoding for Efficient LLM Inference
Locality and Compositionality in Zero-Shot Learning
Dimensionality Reduction for Representing the Knowledge of Probabilistic Models
Bayesian WeakS-to-Strong from Text Classification to Generation
Unbiased Online Recurrent Optimization
Guiding continuous operator learning through Physics-based boundary constraints
Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration
Diffusion Sampling with Momentum for Mitigating Divergence Artifacts
Human-Guided Fair Classification for Natural Language Processing
Learning to Communicate Through Implicit Communication Channels
GraphZoom: A Multi-level Spectral Approach for Accurate and Scalable Graph Embedding
Training Recurrent Neural Networks Online by Learning Explicit State Variables
Complete and Efficient Graph Transformers for Crystal Material Property Prediction
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models
TaskPrompter: Spatial-Channel Multi-Task Prompting for Dense Scene Understanding
Integrative Decoding: Improving Factuality via Implicit Self-consistency
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
PianoMotion10M: Dataset and Benchmark for Hand Motion Generation in Piano Performance
Decoupling Dynamics and Reward for Transfer Learning
UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
A Rate-Distortion View on Model Updates
Many-Objective Multi-Solution Transport
Almost Optimal Batch-Regret Tradeoff for Batch Linear Contextual Bandits
3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings
Harmonic Unpaired Image-to-image Translation
Unifying Causal Representation Learning with the Invariance Principle
Gradient correlation is a key ingredient to accelerate SGD with momentum
Scaffolding a Student to Instill Knowledge
SparseFormer: Sparse Visual Recognition via Limited Latent Tokens
Grounding Video Models to Actions through Goal Conditioned Exploration
PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization
ED-NeRF: Efficient Text-Guided Editing of 3D Scene With Latent Space NeRF
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes
Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning
In-Context Editing: Learning Knowledge from Self-Induced Distributions
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning
MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models
ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation Fusion
Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs
Emergence of meta-stable clustering in mean-field transformer models
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning
D-CODE: Discovering Closed-form ODEs from Observed Trajectories
Does Spatial Cognition Emerge in Frontier Models?
Magnetic Preference Optimization: Achieving Last-iterate Convergence for Language Model Alignment
SPIGAN: Privileged Adversarial Learning from Simulation
Continual Learning with Adaptive Weights (CLAW)
Agent-to-Sim: Learning Interactive Behavior Models from Casual Longitudinal Videos
TRACTABLE LARGE SCALE CALIBRATION WITH RL
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function
Mirage: Model-agnostic Graph Distillation for Graph Classification
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks
DynaVol: Unsupervised Learning for Dynamic Scenes through Object-Centric Voxelization
Sharpness-Aware Data Poisoning Attack
Generating Likely Counterfactuals Using Sum-Product Networks
Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data
SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning
View Synthesis with Sculpted Neural Points
Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs
Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness
Understanding Embodied Reference with Touch-Line Transformer
Learning Factorized Multimodal Representations
Extending the WILDS Benchmark for Unsupervised Adaptation
TabR: Tabular Deep Learning Meets Nearest Neighbors
Memory-Based Graph Networks
Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators
Training wide residual networks for deployment using a single bit for each weight
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards
Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models
Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation
Efficient local linearity regularization to overcome catastrophic overfitting
Generative Question Answering: Learning to Answer the Whole Question
Rethinking Supervised Pre-Training for Better Downstream Transferring
Visual Classification via Description from Large Language Models
Robust Algorithms on Adaptive Inputs from Bounded Adversaries
Characterizing the Influence of Graph Elements
Defending Against Image Corruptions Through Adversarial Augmentations
Unsupervised Discovery of Parts, Structure, and Dynamics
GaussianBlock: Building Part-Aware Compositional and Editable 3D Scene by Primitives and Gaussians
Understanding the Loss Surface of Single-Layered Neural Networks for Binary Classification
Practical Real Time Recurrent Learning with a Sparse Approximation
Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier
RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data
Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors
Neuro-Symbolic Program Synthesis
Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy
Ensemble Distribution Distillation
Efficient Discrete Multi Marginal Optimal Transport Regularization
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning
Training Structured Neural Networks Through Manifold Identification and Variance Reduction
Active Learning for Object Detection with Evidential Deep Learning and Hierarchical Uncertainty Aggregation
DreamCatalyst: Fast and High-Quality 3D Editing via Controlling Editability and Identity Preservation
A Generalized Weighted Optimization Method for Computational Learning and Inversion
FLOPS: Forward Learning with OPtimal Sampling
Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models
MaestroMotif: Skill Design from Artificial Intelligence Feedback
Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation
CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations
Learning advanced mathematical computations from examples
Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets
RFWave: Multi-band Rectified Flow for Audio Waveform Reconstruction
Space and time continuous physics simulation from partial observations
Bag of Tricks for Unsupervised Text-to-Speech
Parallelizing Linear Recurrent Neural Nets Over Sequence Length
Efficient Generalized Spherical CNNs
Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks
Towards Understanding Why Mask Reconstruction Pretraining Helps in Downstream Tasks
SEPT: Towards Efficient Scene Representation Learning for Motion Prediction
Meta Learning Low Rank Covariance Factors for Energy Based Deterministic Uncertainty
Rotated Runtime Smooth: Training-Free Activation Smoother for accurate INT4 inference
Supervised Knowledge Makes Large Language Models Better In-context Learners
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts
Towards Robust Feature Learning with t-vFM Similarity for Continual Learning
Improving Domain Generalization with Domain Relations
DLEFT-MKC: Dynamic Late Fusion Multiple Kernel Clustering with Robust Tensor Learning via Min-Max Optimization
Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors
Q-Adapter: Customizing Pre-trained LLMs to New Preferences with Forgetting Mitigation
Zipformer: A faster and better encoder for automatic speech recognition
Learning Weakly-supervised Contrastive Representations
MetaMetrics: Calibrating Metrics for Generation Tasks Using Human Preferences
DDM 2 : Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models
Early Stopping Against Label Noise Without Validation Data
GReaTer: Gradients Over Reasoning Makes Smaller Language Models Strong Prompt Optimizers
A Light Spectrometer Device for Crop Disease Monitoring
Universal Approximation with Certified Networks
Latent Normalizing Flows for Many-to-Many Cross-Domain Mappings
Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network
Synaptic Weight Distributions Depend on the Geometry of Plasticity
Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching
Coreset Spectral Clustering
Fast Imitation via Behavior Foundation Models
Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games
EigenGame: PCA as a Nash Equilibrium
A Compare-Aggregate Model for Matching Text Sequences
How Powerful are Graph Neural Networks?
Graph Lottery Ticket Automated
Causally Aligned Curriculum Learning
FlashRNN: I/O-Aware Optimization of Traditional RNNs on modern hardware
FedInverse: Evaluating Privacy Leakage in Federated Learning
TAda! Temporally-Adaptive Convolutions for Video Understanding
Offline Reinforcement Learning with Value-based Episodic Memory
Boosted Curriculum Reinforcement Learning
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models
BA-Net: Dense Bundle Adjustment Networks
SPIRAL: Self-supervised Perturbation-Invariant Representation Learning for Speech Pre-Training
Continual learning with hypernetworks
Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics
Hyper-Connections
Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video
Mitigating Object Hallucination in MLLMs via Data-augmented Phrase-level Alignment
Locality Alignment Improves Vision-Language Models
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve
Latent Convergent Cross Mapping
Pseudo-label Training and Model Inertia in Neural Machine Translation
MonoDistill: Learning Spatial Features for Monocular 3D Object Detection