yusuke1997/dblp-id-title huggingface dataset:
RelGAN: Relational Generative Adversarial Networks for Text Generation
Context Mover's Distance & Barycenters: Optimal transport of contexts for building representations
Diffusion-GAN: Training GANs with Diffusion
Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot Learning
InterLCM: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration
MatryoshkaKV: Adaptive KV Compression via Trainable Orthogonal Projection
Learning Hierarchical Protein Representations via Complete 3D Graph Networks
Sin3DM: Learning a Diffusion Model from a Single 3D Textured Shape
Anti-Concentrated Confidence Bonuses For Scalable Exploration
Modeling state-dependent communication between brain regions with switching nonlinear dynamical systems
Minimalistic Predictions for Online Class Constraint Scheduling
Exploring The Loss Landscape Of Regularized Neural Networks Via Convex Duality
Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups
Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning
GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks
Generating Pragmatic Examples to Train Neural Program Synthesizers
Heavy-Tailed Diffusion with Denoising Levy Probabilistic Models
Semi-supervised learning with a principled likelihood from a generative model of data curation
Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research
Dive Deeper Into Integral Pose Regression
Multiplicative Filter Networks
Rethinking Label Poisoning for GNNs: Pitfalls and Attacks
Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation
Learning by Directional Gradient Descent
How Does Critical Batch Size Scale in Pre-training?
Discriminator-Guided Embodied Planning for LLM Agent
Gaussian Head & Shoulders: High Fidelity Neural Upper Body Avatars with Anchor Gaussian Guided Texture Warping
Betty: An Automatic Differentiation Library for Multilevel Optimization
Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training
How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks?
Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling
DiffEdit: Diffusion-based semantic image editing with mask guidance
Expected flow networks in stochastic environments and two-player zero-sum games
Collab: Controlled Decoding using Mixture of Agents for LLM Alignment
Temporally Efficient Deep Learning with Spikes
On the Weaknesses of Reinforcement Learning for Neural Machine Translation
Frame Averaging for Invariant and Equivariant Network Design
Improving Generative Adversarial Networks with Denoising Feature Matching
Deconstructing What Makes a Good Optimizer for Autoregressive Language Models
Adversarial Training Should Be Cast as a Non-Zero-Sum Game
Periodicity Decoupling Framework for Long-term Series Forecasting
Proving Test Set Contamination in Black-Box Language Models
Bayesian Experimental Design Via Contrastive Diffusions
Compound Tokens: Channel Fusion for Vision-Language Representation Learning
Feedback Favors the Generalization of Neural ODEs
Variational Recurrent Adversarial Deep Domain Adaptation
Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning
Towards Best Practices of Activation Patching in Language Models: Metrics and Methods
Calibrating Energy-based Generative Adversarial Networks
Conditional Variational Diffusion Models
Look Before You Leap: Universal Emergent Mechanism for Retrieval in Language Models
Jacobian Adversarially Regularized Networks for Robustness
GradMax: Growing Neural Networks using Gradient Information
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method
On the Crucial Role of Initialization for Matrix Factorization
Neural Spectral Marked Point Processes
Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models
Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models
Towards One-shot Neural Combinatorial Solvers: Theoretical and Empirical Notes on the Cardinality-Constrained Case
Rotation-invariant clustering of neuronal responses in primary visual cortex
Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis
Neural Contractive Dynamical Systems
Regretful Decisions under Label Noise
DM-NeRF: 3D Scene Geometry Decomposition and Manipulation from 2D Images
Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation
Geometry-aware Instance-reweighted Adversarial Training
TopoLM: brain-like spatio-functional organization in a topographic language model
Fair Clustering in the Sliding Window Model
Mixture Compressor for Mixture-of-Experts LLMs Gains More
Reinforcement learning with combinatorial actions for coupled restless bandits
The Expressive Power of Transformers with Chain of Thought
Let the Code LLM Edit Itself When You Edit the Code
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization
Topological Zigzag Spaghetti for Diffusion-based Generation and Prediction on Graphs
A Neural Mean Embedding Approach for Back-door and Front-door Adjustment
Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning
Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration
MaGIC: Multi-modality Guided Image Completion
Removing Biases from Molecular Representations via Information Maximization
Bridging the Data Provenance Gap Across Text, Speech, and Video
ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning
DUALFormer: Dual Graph Transformer
Leveraging Uncertainty Estimates To Improve Classifier Performance
Lie Group Decompositions for Equivariant Neural Networks
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip
Accessing Vision Foundation Models via ImageNet-1K
#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models
CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning
Reducing Transformer Depth on Demand with Structured Dropout
A path-norm toolkit for modern networks: consequences, promises and challenges
Valid Conformal Prediction for Dynamic GNNs
Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective
AdvectiveNet: An Eulerian-Lagrangian Fluidic Reservoir for Point Cloud Processing
Clustering Meets Implicit Generative Models
CaPo: Cooperative Plan Optimization for Efficient Embodied Multi-Agent Cooperation
Active Learning for Continual Learning: Keeping the Past Alive in the Present
ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
Optimizer Amalgamation
Operator Deep Smoothing for Implied Volatility
Multi-Resolution Decomposable Diffusion Model for Non-Stationary Time Series Anomaly Detection
Spectral Inference Networks: Unifying Deep and Spectral Learning
Koopman-based generalization bound: New aspect for full-rank weights
Aligning AI With Shared Human Values
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs
Neurally Augmented ALISTA
Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL
Goal-Directed Planning via Hindsight Experience Replay
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
Deja Vu: Continual Model Generalization for Unseen Domains
Selective Annotation Makes Language Models Better Few-Shot Learners
On the Convergence of Certified Robust Training with Interval Bound Propagation
Declarative nets that are equilibrium models
Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think
Interactive Grounded Language Acquisition and Generalization in a 2D World
Neural Architecture Design and Robustness: A Dataset
Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation
HyperDynamics: Meta-Learning Object and Agent Dynamics with Hypernetworks
RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems
Beyond Random Masking: When Dropout meets Graph Convolutional Networks
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing
Long-tailed Recognition by Routing Diverse Distribution-Aware Experts
Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization
Self-Alignment with Instruction Backtranslation
Causal-StoNet: Causal Inference for High-Dimensional Complex Data
General Scene Adaptation for Vision-and-Language Navigation
ReAttention: Training-Free Infinite Context with Finite Attention Scope
DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks
Robust Simulation-Based Inference under Missing Data via Neural Processes
TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes
Large Language Models are Human-Level Prompt Engineers
QAID: Question Answering Inspired Few-shot Intent Detection
Searching for High-Value Molecules Using Reinforcement Learning and Transformers
Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions
On the Completeness of Invariant Geometric Deep Learning Models
Active Task Disambiguation with LLMs
Inference Scaling for Long-Context Retrieval Augmented Generation
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case
Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition
HaDeMiF: Hallucination Detection and Mitigation in Large Language Models
Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy
Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators
KLay: Accelerating Arithmetic Circuits for Neurosymbolic AI
Do Not Escape From the Manifold: Discovering the Local Coordinates on the Latent Space of GANs
DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving
More RLHF, More Trust? On The Impact of Preference Alignment On Trustworthiness
Scene Transformer: A unified architecture for predicting future trajectories of multiple agents
On the Optimization and Generalization of Two-layer Transformers with Sign Gradient Descent
Differentiable Neural Network Architecture Search
Viewmaker Networks: Learning Views for Unsupervised Representation Learning
Stability Regularization for Discrete Representation Learning
Information-Theoretic Diffusion
AutoCGP: Closed-Loop Concept-Guided Policies from Unlabeled Demonstrations
Towards Realistic UAV Vision-Language Navigation: Platform, Benchmark, and Methodology
CHiP: Cross-modal Hierarchical Direct Preference Optimization for Multimodal LLMs
Bandits with Replenishable Knapsacks: the Best of both Worlds
Learnable Embedding sizes for Recommender Systems
ZipIt! Merging Models from Different Tasks without Training
Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces
Transferring Knowledge across Learning Processes
The Geometry of Multilingual Language Models: An Equality Lens
A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels
Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond
On the Reliability of Watermarks for Large Language Models
Retrieval meets Long Context Large Language Models
Precise Recovery of Latent Vectors from Generative Adversarial Networks
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions
Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN
On the Origin of Implicit Regularization in Stochastic Gradient Descent
Exploiting Distribution Constraints for Scalable and Efficient Image Retrieval
GATSBI: Generative Adversarial Training for Simulation-Based Inference
CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception
Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search
Image Inpainting via Tractable Steering of Diffusion Models
Evaluating the Efficacy of Federated Scoring Systems with Heterogeneous Electronic Health Records
Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset
Chain of Hindsight aligns Language Models with Feedback
Stable and Effective Trainable Greedy Decoding for Sequence to Sequence Learning
Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration
SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistency
Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
Offline Congestion Games: How Feedback Type Affects Data Coverage Requirement
Domain Randomization via Entropy Maximization
Instant3D: Fast Text-to-3D with Sparse-view Generation and Large Reconstruction Model
Heat Up The Sentiment Learning With ICE
Understanding prompt engineering may not require rethinking generalization
TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies
Learning to Share: simultaneous parameter tying and Sparsification in Deep Learning
A Novel Sector-Based Algorithm for an Optimized Star-Galaxy Classification
How many degrees of freedom do we need to train deep networks: a loss landscape perspective
Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-Free RL
Simple and Scalable Nearest Neighbor Machine Translation
Compositional Semantic Parsing with Large Language Models
Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning
Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks
Offensiveness as an Opinion: Dissecting population-level Label Distributions
Regularizing CNNs with Locally Constrained Decorrelations
CMFPN: Context Modeling Meets Feature Pyramid Network
Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning
Learning To Simulate
Synapse: Trajectory-as-Exemplar Prompting with Memory for Computer Control
Equivariant Subgraph Aggregation Networks
Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data
OSDA Agent: Leveraging Large Language Models for De Novo Design of Organic Structure Directing Agents
Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search
Adaptive Rational Activations to Boost Deep Reinforcement Learning
Heavy-Tailed Diffusion Models
Bridging Neural and Symbolic Representations with Transitional Dictionary Learning
On the Connection between Local Attention and Dynamic Depth-wise Convolution
Accelerating Training with Neuron Interaction and Nowcasting Networks
Conditional Diffusion with Ordinal Regression: Longitudinal Data Generation for Neurodegenerative Disease Studies
One Explanation Does Not Fit XIL
Generalized Decision Transformer for Offline Hindsight Information Matching
Learning Embeddings into Entropic Wasserstein Spaces
Plastic Learning with Deep Fourier Features
Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport
Probabilistic Planning with Sequential Monte Carlo methods
Revisiting Auxiliary Latent Variables in Generative Models
MMR: A Large-scale Benchmark Dataset for Multi-target and Multi-granularity Reasoning Segmentation
Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics
Optimal Flow Transport and its Entropic Regularization: a GPU-friendly Matrix Iterative Algorithm for Flow Balance Satisfaction
Iformer: Integrating ConvNet and Transformer for Mobile Application
Self-Updatable Large Language Models by Integrating Context into Model Parameters
Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning
Learning protein sequence embeddings using information from structure
Reward Bound for Behavioral Guarantee of Model-based Planning Agents
Towards Improving Exploration through Sibling Augmented GFlowNets
Learning to Remember Rare Events
Spread Preference Annotation: Direct Preference Judgment for Efficient LLM Alignment
Multi-Field Adaptive Retrieval
Vision-Language Foundation Models as Effective Robot Imitators
Region Mixup
Intrinsic User-Centric Interpretability through Global Mixture of Experts
How much of my dataset did you use? Quantitative Data Usage Inference in Machine Learning
Towards Stable and Efficient Training of Verifiably Robust Neural Networks
Amortized Implicit Differentiation for Stochastic Bilevel Optimization
Bandit Learning with Joint Effect of Incentivized Sampling, Delayed Sampling Feedback, and Self-Reinforcing User Preferences
Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning
NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
Monotonic Differentiable Sorting Networks
ComaDICE: Offline Cooperative Multi-Agent Reinforcement Learning with Stationary Distribution Shift Regularization
Effective Self-supervised Pre-training on Low-compute Networks without Distillation
GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion
Neural Probabilistic Motor Primitives for Humanoid Control
Incremental Randomized Smoothing Certification
Hypothesis Search: Inductive Reasoning with Language Models
Hypermodels for Exploration
Convex Formulations for Training Two-Layer ReLU Neural Networks
Learning to Count Objects in Natural Images for Visual Question Answering
Broken Neural Scaling Laws
Class Incremental Learning via Likelihood Ratio Based Task Prediction
Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers
Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing
Tracing Footprints: Neural Networks Meet Non-integer Order Differential Equations For Modelling Systems with Memory
Surreal-GAN: Semi-Supervised Representation Learning via GAN for uncovering heterogeneous disease-related imaging patterns
CHAMP: Conformalized 3D Human Multi-Hypothesis Pose Estimators
Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate
Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension
MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark
Decision Tree Induction Through LLMs via Semantically-Aware Evolution
Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature Attribution
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
OCCAM: Towards Cost-Efficient and Accuracy-Aware Classification Inference
Variational Smoothing in Recurrent Neural Network Language Models
Advancing Out-of-Distribution Detection via Local Neuroplasticity
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark
Bongard-OpenWorld: Few-Shot Reasoning for Free-form Visual Concepts in the Real World
Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization
Taming Transformer Without Using Learning Rate Warmup
Robust Subspace Recovery Layer for Unsupervised Anomaly Detection
Procedural Fairness Through Decoupling Objectionable Data Generating Components
Fundamental limits on the robustness of image classifiers
Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning
A unique M-pattern for micro-expression spotting in long videos
Spreading Out-of-Distribution Detection on Graphs
SPDER: Semiperiodic Damping-Enabled Object Representation
VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly Detection
On the Stability of Expressive Positional Encodings for Graphs
What Makes Better Augmentation Strategies? Augment Difficult but Not too Different
Combining Q-Learning and Search with Amortized Value Estimates
Protecting DNNs from Theft using an Ensemble of Diverse Models
HYPE: Human-eYe Perceptual Evaluation of Generative Models
MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo
Discovering objects and their relations from entangled scene representations
Sign2GPT: Leveraging Large Language Models for Gloss-Free Sign Language Translation
Rethinking Positional Encoding in Language Pre-training
Plateau in Monotonic Linear Interpolation - A "Biased" View of Loss Landscape for Deep Networks
Ae-OT: a New Generative Model based on Extended Semi-discrete Optimal transport
Metacontrol for Adaptive Imagination-Based Optimization
Efficient Inference for Large Language Model-based Generative Recommendation
Precedence-Constrained Winter Value for Effective Graph Data Valuation
MTSAM: Multi-Task Fine-Tuning for Segment Anything Model
Spherical Sliced-Wasserstein
Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose?
Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition
Posterior Attention Models for Sequence to Sequence Learning
Manifold Diffusion Fields
Learning where and when to reason in neuro-symbolic inference
From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data
Conditional Positional Encodings for Vision Transformers
Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks
Deep AutoAugment
Simple Hierarchical Planning with Diffusion
Unifying Feature and Cost Aggregation with Transformers for Semantic and Visual Correspondence
Vision-Based Manipulators Need to Also See from Their Hands
Privacy Implications of Shuffling
Pay Attention to Multi-Channel for Improving Graph Neural Networks
DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models
Minigo: A Case Study in Reproducing Reinforcement Learning Research
NTK-SAP: Improving neural network pruning by aligning training dynamics
Quota Constraints for Diversity Interventions in Subset Selection
Images as Weight Matrices: Sequential Image Generation Through Synaptic Learning Rules
StyleMorph: Disentangled 3D-Aware Image Synthesis with a 3D Morphable StyleGAN
Learning Disentangled Representations for CounterFactual Regression
Making Transformer Decoders Better Differentiable Indexers
A Laplace-inspired Distribution on SO(3) for Probabilistic Rotation Estimation
ELICIT: LLM Augmentation Via External In-context Capability
Data-Efficient Graph Grammar Learning for Molecular Generation
Sequential Latent Variable Models for Few-Shot High-Dimensional Time-Series Forecasting
How Far Are We from True Unlearnability?
Winning Both the Accuracy of Floating Point Activation and the Simplicity of Integer Arithmetic
CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning
Large Language Models Cannot Self-Correct Reasoning Yet
Maximizing Ensemble Diversity in Deep Reinforcement Learning
Learning Multimodal VAEs through Mutual Supervision
Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design
Beyond Graphs: Can Large Language Models Comprehend Hypergraphs?
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks
Ada-K Routing: Boosting the Efficiency of MoE-based LLMs
Decoupled Finetuning for Domain Generalizable Semantic Segmentation
Lossy Compression with Distribution Shift as Entropy Constrained Optimal Transport
Adam-mini: Use Fewer Learning Rates To Gain More
Communication-Efficient Federated Non-Linear Bandit Optimization
VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts
Online Boundary-Free Continual Learning by Scheduled Data Prior
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks