yusuke1997/dblp-id-title huggingface dataset:
Learning Transformer-based World Models with Contrastive Predictive Coding
Fast Task Inference with Variational Intrinsic Successor Features
Discrete Latent Plans via Semantic Skill Abstractions
Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words
Provable Adaptation across Multiway Domains via Representation Learning
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach
Learning Molecular Representation in a Cell
EntQA: Entity Linking as Question Answering
Mind Control through Causal Inference: Predicting Clean Images from Poisoned Data
Dynamic Neural Response Tuning
Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds
Adam Exploits ℓ∞-geometry of Loss Landscape via Coordinate-wise Adaptivity
AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods
Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints
Preserving Diversity in Supervised Fine-Tuning of Large Language Models
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition
Object Pursuit: Building a Space of Objects via Discriminative Weight Generation
Beyond calibration: estimating the grouping loss of modern neural networks
Thieves on Sesame Street! Model Extraction of BERT-based APIs
An Adaptive Policy to Employ Sharpness-Aware Minimization
Federated Wasserstein Distance
The Convex Geometry of Backpropagation: Neural Network Gradient Flows Converge to Extreme Points of the Dual Convex Program
Improving Pretraining Data Using Perplexity Correlations
Viterbi-based Pruning for Sparse Matrix with Fixed and High Index Compression Ratio
NoVo: Norm Voting off Hallucinations with Attention Heads in Large Language Models
Empirical Risk Landscape Analysis for Understanding Deep Neural Networks
Discrete Graph Structure Learning for Forecasting Multiple Time Series
Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms
Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD
Multi-Time Attention Networks for Irregularly Sampled Time Series
Aria-MIDI: A Dataset of Piano MIDI Files for Symbolic Music Modeling
Improving Neural Language Generation with Spectrum Control
VONet: Unsupervised Video Object Learning With Parallel U-Net Attention and Object-wise Sequential VAE
Conditional Antibody Design as 3D Equivariant Graph Translation
Colorization Transformer
Hierarchical World Models as Visual Whole-Body Humanoid Controllers
Learning Cross-Domain Correspondence for Control with Dynamics Cycle-Consistency
The Provable Benefit of Unsupervised Data Sharing for Offline Reinforcement Learning
Learning to Optimize
Enhancing Document Understanding with Group Position Embedding: A Novel Approach to Incorporate Layout Information
Learning to Infer
True Knowledge Comes from Practice: Aligning Large Language Models with Embodied Environments via Reinforcement Learning
Selective Task Group Updates for Multi-Task Optimization
GRAND++: Graph Neural Diffusion with A Source Term
Understanding and Robustifying Differentiable Architecture Search
A Geometric Framework for Understanding Memorization in Generative Models
Denoising Masked Autoencoders Help Robust Classification
The Curious Case of Benign Memorization
Repelling Random Walks
NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling
Neural Compositional Rule Learning for Knowledge Graph Reasoning
Diagnosing and Enhancing VAE Models
Towards Foundation Models for Knowledge Graph Reasoning
SmartRAG: Jointly Learn RAG-Related Tasks From the Environment Feedback
Graph-constrained diffusion for End-to-End Path Planning
SPTNet: An Efficient Alternative Framework for Generalized Category Discovery with Spatial Prompt Tuning
UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery
The Responsibility Problem in Neural Networks with Unordered Targets
Whitening and Coloring Batch Transform for GANs
Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach
Disentangling 3D Prototypical Networks for Few-Shot Concept Learning
Estimating Gradients for Discrete Random Variables by Sampling without Replacement
Semi-supervised deep learning by metric embedding
Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue System
Verification of Non-Linear Specifications for Neural Networks
VOS: Learning What You Don't Know by Virtual Outlier Synthesis
LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification
TeaserGen: Generating Teasers for Long Documentaries
A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
Expressivity of Neural Networks with Random Weights and Learned Biases
Demonstration-Regularized RL
CEM-RL: Combining evolutionary and gradient-based methods for policy search
Complex Query Answering with Neural Link Predictors
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity
MaskedFusion360: Reconstruct LiDAR Data by Querying Camera Features
Noise or Signal: The Role of Image Backgrounds in Object Recognition
Robustifying State-space Models for Long Sequences via Approximate Diagonalization
On a Connection Between Imitation Learning and RLHF
TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models
Group-robust Sample Reweighting for Subpopulation Shifts via Influence Functions
Meta-Dynamical State Space Models for Integrative Neural Data Analysis
Deep Generative Models for Generating Labeled Graphs
Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis--Hastings
Achieving Human Parity in Content-Grounded Datasets Generation
WikiWhy: Answering and Explaining Cause-and-Effect Questions
Characterizing the spectrum of the NTK via a power series expansion
On the Relation between Trainability and Dequantization of Variational Quantum Learning Models
BingoGuard: LLM Content Moderation Tools with Risk Levels
Generative Models for Effective ML on Private, Decentralized Datasets
Shot2Story: A New Benchmark for Comprehensive Understanding of Multi-shot Videos
Out-of-Distribution Detection with Negative Prompts
Towards Faithful Explanations: Boosting Rationalization with Shortcuts Discovery
BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity Allocation
Breaking the Reclustering Barrier in Centroid-based Deep Clustering
WiNeRT: Towards Neural Ray Tracing for Wireless Channel Modelling and Differentiable Simulations
An interpretable LSTM neural network for autoregressive exogenous model
Precise Localization of Memories: A Fine-grained Neuron-level Knowledge Editing Technique for LLMs
Stochastic Neural Networks for Hierarchical Reinforcement Learning
Generating Images with 3D Annotations Using Diffusion Models
EditRoom: LLM-parameterized Graph Diffusion for Composable 3D Room Layout Editing
Towards Impartial Multi-task Learning
MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space
GitGraph - from Computational Subgraphs to Smaller Architecture Search Spaces
Symmetric Single Index Learning
Stiefel Flow Matching for Moment-Constrained Structure Elucidation
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks
Test-Time Adaptation for Combating Missing Modalities in Egocentric Videos
Learning to Guide Random Search
Hierarchical Variational Memory for Few-shot Learning Across Domains
Cognitive Reframing via Large Language Models for Enhanced Linguistic Attributes
Symbolic Learning to Optimize: Towards Interpretability and Scalability
Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems
ISS: Image as Stepping Stone for Text-Guided 3D Shape Generation
Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement
Unbiased Contrastive Divergence Algorithm for Training Energy-Based Latent Variable Models
Global Identifiability of Overcomplete Dictionary Learning via L1 and Volume Minimization
Mosaic Representation Learning for Self-supervised Visual Pre-training
Towards Unified Human Motion-Language Understanding via Sparse Interpretable Characterization
Label Encoding for Regression Networks
MambaPEFT: Exploring Parameter-Efficient Fine-Tuning for Mamba
Personalized Visual Instruction Tuning
You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings
Gradient Boosting Performs Gaussian Process Inference
LambdaNet: Probabilistic Type Inference using Graph Neural Networks
Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time-Series Forecasting Based on Biological ODEs
Programmatically Grounded, Compositionally Generalizable Robotic Manipulation
BALTO: fast tensor program optimization with diversity-based active learning
Fast Value Tracking for Deep Reinforcement Learning
Categorical Normalizing Flows via Continuous Transformations
Soft Q-Learning with Mutual-Information Regularization
Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularization
MorphoDiff: Cellular Morphology Painting with Diffusion Models
Understanding and Improving Information Transfer in Multi-Task Learning
Coping with Label Shift via Distributionally Robust Optimisation
Track-On: Transformer-based Online Point Tracking with Memory
Revisiting Large-Scale Non-convex Distributionally Robust Optimization
Learning Object-Oriented Dynamics for Planning from Text
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
UL2: Unifying Language Learning Paradigms
On Generalization Across Environments In Multi-Objective Reinforcement Learning
Broaden your SCOPE! Efficient Multi-turn Conversation Planning for LLMs with Semantic Space
From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF
A Large-scale Dataset and Benchmark for Commuting Origin-Destination Flow Generation
Unsupervised Hyper-alignment for Multilingual Word Embeddings
Self-Improving Robust Preference Optimization
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation
Transport meets Variational Inference: Controlled Monte Carlo Diffusions
CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models
AdaAug: Learning Class- and Instance-adaptive Data Augmentation Policies
Stem-OB: Generalizable Visual Imitation Learning with Stem-Like Convergent Observation through Diffusion Inversion
Understanding the Limitations of Conditional Generative Models
A deep inverse-mapping model for a flapping robotic wing
Provably robust classification of adversarial examples with detection
PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets
Score-based free-form architectures for high-dimensional Fokker-Planck equations
Identifying Analogies Across Domains
Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks
Improving Instruction-Following in Language Models through Activation Steering
URLOST: Unsupervised Representation Learning without Stationarity or Topology
On Position Embeddings in BERT
Adversarial Policy Gradient for Learning Graph-Based Representation in Human Visual Processing
Joint Gradient Balancing for Data Ordering in Finite-Sum Multi-Objective Optimization
SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning
Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality
OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code
An Exploration with Entropy Constrained 3D Gaussians for 2D Video Compression
Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems
Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics
IsarStep: a Benchmark for High-level Mathematical Reasoning
Q-Learning as a montone scheme
Vitruvion: A Generative Model of Parametric CAD Sketches
Learn Your Reference Model for Real Good Alignment
Is Importance Weighting Incompatible with Interpolating Classifiers?
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications
Improved Approximation Algorithms for k-Submodular Maximization via Multilinear Extension
Towards Homogeneous Lexical Tone Decoding from Heterogeneous Intracranial Recordings
Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts?
Polar Transformer Networks
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery
Better Supervisory Signals by Observing Learning Paths
Adapting Multi-modal Large Language Model to Concept Drift From Pre-training Onwards
Delving into Semantic Scale Imbalance
ImaginaryNet: Learning Object Detectors without Real Images and Annotations
Consistent4D: Consistent 360° Dynamic Object Generation from Monocular Video
Brain-like representational straightening of natural movies in robust feedforward neural networks
From Posterior Sampling to Meaningful Diversity in Image Restoration
InCoDe: Interpretable Compressed Descriptions For Image Generation
Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry
Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization
Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation
A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease
Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
Bellman Optimal Stepsize Straightening of Flow-Matching Models
Benchmarking LLMs' Judgments with No Gold Standard
Learning Multi-Agent Communication with Contrastive Learning
DiffusER: Diffusion via Edit-based Reconstruction
Dissecting Zero-Shot Visual Reasoning Capabilities in Vision and Language Models
Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference
Revealing and Mitigating Over-Attention in Knowledge Editing
Skip Connections Eliminate Singularities
GeoILP: A Synthetic Dataset to Guide Large-Scale Rule Induction
Causal Contextual Bandits with Targeted Interventions
MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL
Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning
Self-Supervised Policy Adaptation during Deployment
Reward Design for Justifiable Sequential Decision-Making
Systematic Weight Pruning of DNNs using Alternating Direction Method of Multipliers
PAC Prediction Sets Under Label Shift
Anytime Sampling for Autoregressive Models via Ordered Autoencoding
Revisiting Batch Normalization For Practical Domain Adaptation
Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models
Learning to solve Class-Constrained Bin Packing Problems via Encoder-Decoder Model
Information Retention via Learning Supplemental Features
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference
Measuring Massive Multitask Language Understanding
Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models
Generative Modeling Helps Weak Supervision (and Vice Versa)
Block Verification Accelerates Speculative Decoding
MoDeGPT: Modular Decomposition for Large Language Model Compression
Latent Skill Planning for Exploration and Transfer
Flow Matching for Generative Modeling
DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing
Self-Supervised High Dynamic Range Imaging with Multi-Exposure Images in Dynamic Scenes
Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy Hessians
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond
GPS: A Probabilistic Distributional Similarity with Gumbel Priors for Set-to-Set Matching
SONICS: Synthetic Or Not - Identifying Counterfeit Songs
R&B: Region and Boundary Aware Zero-shot Grounded Text-to-image Generation
CBQ: Cross-Block Quantization for Large Language Models
Network Pruning That Matters: A Case Study on Retraining Variants
Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems
Neuroplastic Expansion in Deep Reinforcement Learning
Glauber Generative Model: Discrete Diffusion Models via Binary Classification
Precise Parameter Localization for Textual Generation in Diffusion Models
Boosting Latent Diffusion with Perceptual Objectives
Understanding Domain Generalization: A Noise Robustness Perspective
Learned Index with Dynamic $\epsilon$
DC3: A learning method for optimization with hard constraints
Recursive Reasoning with Neural Networks
Monte Carlo Planning with Large Language Model for Text-Based Game Agents
Preconditioner on Matrix Lie Group for SGD
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
Deep Semi-Supervised Anomaly Detection
Efficient Score Matching with Deep Equilibrium Layers
DDMI: Domain-agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations
Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathology
Theoretical Understanding of Learning from Adversarial Perturbations
Learning to Help in Multi-Class Settings
Kronecker-factored Curvature Approximations for Recurrent Neural Networks
On Stationary Point Convergence of PPO-Clip
Neural Speed Reading with Structural-Jump-LSTM
Charformer: Fast Character Transformers via Gradient-based Subword Tokenization
Improving Probabilistic Diffusion Models With Optimal Diagonal Covariance Matching
Test-time Alignment of Diffusion Models without Reward Over-optimization
Towards Lightweight, Model-Agnostic and Diversity-Aware Active Anomaly Detection
Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis
SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem
Optimal Representations for Covariate Shift
Efficient Planning with Latent Diffusion
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction
GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models
Safety-Prioritizing Curricula for Constrained Reinforcement Learning
ComLoRA: A Competitive Learning Approach for Enhancing LoRA
When should we prefer Decision Transformers for Offline Reinforcement Learning?
On the Generalization and Approximation Capacities of Neural Controlled Differential Equations
Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning
LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors
Fast Summation of Radial Kernels via QMC Slicing
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework
Detecting, Explaining, and Mitigating Memorization in Diffusion Models
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data
BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models
Distributional Concavity Regularization for GANs
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation
Exploring the cloud of feature interaction scores in a Rashomon set
Generative Time-series Modeling with Fourier Flows
TOMATO: Assessing Visual Temporal Reasoning Capabilities in Multimodal Foundation Models
Neural Models for Output-Space Invariance in Combinatorial Problems
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training
MgNO: Efficient Parameterization of Linear Operators via Multigrid
Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks
Autoregressive Diffusion Models
Generalisation in Lifelong Reinforcement Learning through Logical Composition
Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction
Scaling Laws for a Multi-Agent Reinforcement Learning Model
What shapes the loss landscape of self supervised learning?
A Statistical Approach for Controlled Training Data Detection
DarkBench: Benchmarking Dark Patterns in Large Language Models
Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications
Forgetting Transformer: Softmax Attention with a Forget Gate
Robust Conditional Generative Adversarial Networks
The Efficiency Misnomer
Learning how to explain neural networks: PatternNet and PatternAttribution
Neural Sampling from Boltzmann Densities: Fisher-Rao Curves in the Wasserstein Geometry
GOOD: Exploring geometric cues for detecting objects in an open world
Autonomous Generation of Innovative Content by Multi-Agent System
Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors
mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models
Generative Verifiers: Reward Modeling as Next-Token Prediction
Constraining Linear-chain CRFs to Regular Languages
Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL
Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension
Inherently Interpretable Time Series Classification via Multiple Instance Learning
Auxiliary Task Update Decomposition: the Good, the Bad and the neutral
Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders
JPEG Inspired Deep Learning
Compressing Latent Space via Least Volume
Combinatorial Bandits for Maximum Value Reward Function under Value-Index Feedback
Learning Structured Universe Graph with Outlier OOD Detection for Partial Matching
Homomorphism Counts as Structural Encodings for Graph Learning
SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understanding
Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing
What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?
Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning
On Bonus Based Exploration Methods In The Arcade Learning Environment
Phenomenology of Double Descent in Finite-Width Neural Networks
LAMOL: LAnguage MOdeling for Lifelong Language Learning
Software 1.0 Strengths for Interpretability and Data Efficiency
CLIPDrag: Combining Text-based and Drag-based Instructions for Image Editing
AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models
On Accelerated Perceptrons and Beyond
Riemannian Metric Learning via Optimal Transport
DensePure: Understanding Diffusion Models for Adversarial Robustness
Unsupervised Semantic Segmentation by Distilling Feature Correspondences
3D-FilterMap: A Compact Architecture for Deep Convolutional Neural Networks
Can Watermarks be Used to Detect LLM IP Infringement For Free?
Provably Robust Adversarial Examples
Limits to scalable evaluation at the frontier: LLM as judge won't beat twice the data
When does compositional structure yield compositional generalization? A kernel theory
Everything is Editable: Extend Knowledge Editing to Unstructured Data in Large Language Models
Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints
LVSM: A Large View Synthesis Model with Minimal 3D Inductive Bias
OpenRCA: Can Large Language Models Locate the Root Cause of Software Failures?
Democratic Training Against Universal Adversarial Perturbations
Learning Optimal Conformal Classifiers
From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series
HoloNets: Spectral Convolutions do extend to Directed Graphs
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
Feature-Wise Bias Amplification