yusuke1997/dblp-id-title huggingface dataset:
Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature
Learning concise representations for regression by evolving networks of trees
VTNet: Visual Transformer Network for Object Goal Navigation
Over-parameterized Model Optimization with Polyak-Łojasiewicz Condition
Causal Effect Estimation with Mixed Latent Confounders and Post-treatment Variables
Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking
Statistical Advantages of Perturbing Cosine Router in Mixture of Experts
Fast Ensembling with Diffusion Schrödinger Bridge
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning
Fixed Neural Network Steganography: Train the images, not the network
An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization
Synthetic Controls as Balancing Scores
Amortized Bayesian Meta-Learning
Masked Based Unsupervised Content Transfer
Learning Exploration Policies for Navigation
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback
Open-World Semi-Supervised Learning
DailyDilemmas: Revealing Value Preferences of LLMs with Quandaries of Daily Life
IceFormer: Accelerated Inference with Long-Sequence Transformers on CPUs
Time Travel in LLMs: Tracing Data Contamination in Large Language Models
Rethinking the role of frames for SE(3)-invariant crystal structure modeling
Revisiting Classifier Two-Sample Tests
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning
The robustness of differentiable Causal Discovery in misspecified Scenarios
SELF: Learning to Filter Noisy Labels with Self-Ensembling
Talking Turns: Benchmarking Audio Foundation Models on Turn-Taking Dynamics
Is uniform expressivity too restrictive? Towards efficient expressivity of GNNs
Towards Interpretable Deep Reinforcement Learning with Human-Friendly Prototypes
The Geometry of Memoryless Stochastic Policy Optimization in Infinite-Horizon POMDPs
Semi-supervised Keypoint Localization
Joint Graph Rewiring and Feature Denoising via Spectral Resonance
Estimating counterfactual treatment outcomes over time through adversarially balanced representations
Holistic Reasoning with Long-Context LMs: A Benchmark for Database Operations on Massive Textual Data
Input Space Mode Connectivity in Deep Neural Networks
Critical Learning Periods Emerge Even in Deep Linear Networks
Geodesic Mode Connectivity
Monotonic models for real-time dynamic malware detection
Deep Random Features for Scalable Interpolation of Spatiotemporal Data
MARKOVIAN EMBEDDINGS FOR COALITIONAL BARGAINING GAMES
Multi-Task Learning for Document Ranking and Query Suggestion
StructRAG: Boosting Knowledge Intensive Reasoning of LLMs via Inference-time Hybrid Information Structurization
X-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
PV3D: A 3D Generative Model for Portrait Video Generation
Multilingual Neural Machine Translation With Soft Decoupled Encoding
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
Scaling Laws for Associative Memories
Approximation algorithms for combinatorial optimization with predictions
Learning Intrinsic Sparse Structures within Long Short-Term Memory
Tree-structured decoding with doubly-recurrent neural networks
Uncertainty Quantification via Stable Distribution Propagation
Fugatto 1: Foundational Generative Audio Transformer Opus 1
Revisiting Pruning at Initialization Through the Lens of Ramanujan Graph
Out-of-Distribution Detection and Selective Generation for Conditional Language Models
A New Perspective on "How Graph Neural Networks Go Beyond Weisfeiler-Lehman?"
Event-Driven Online Vertical Federated Learning
Lipschitz Singularities in Diffusion Models
Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations
Weighted Geodesic Distance Following Fermat's Principle
LLM-wrapper: Black-Box Semantic-Aware Adaptation of Vision-Language Models for Referring Expression Comprehension
Efficient Low-Bit Quantization with Adaptive Scales for Multi-Task Co-Training
Non-Parallel Text Style Transfer with Self-Parallel Supervision
Free Lunch for Domain Adversarial Training: Environment Label Smoothing
Sample Efficient Imitation Learning for Continuous Control
Adapters for Altering LLM Vocabularies: What Languages Benefit the Most?
A Training-Free Sub-quadratic Cost Transformer Model Serving Framework with Hierarchically Pruned Attention
Metric-Driven Attributions for Vision Transformers
Multimarginal Generative Modeling with Stochastic Interpolants
Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect
Discovery of Natural Language Concepts in Individual Units of CNNs
Exploring Target Representations for Masked Autoencoders
D-FINE: Redefine Regression Task of DETRs as Fine-grained Distribution Refinement
SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory
ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks
Sampling-based inference for large linear models, with application to linearised Laplace
In-context Reinforcement Learning with Algorithm Distillation
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions
ELBOing Stein: Variational Bayes with Stein Mixture Inference
RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch
Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint
TPU-GAN: Learning temporal coherence from dynamic point cloud sequences
Super(ficial)-alignment: Strong Models May Deceive Weak Models in Weak-to-Strong Generalization
Emergent Symbols through Binding in External Memory
INS: Interaction-aware Synthesis to Enhance Offline Multi-agent Reinforcement Learning
Interpretable Diffusion via Information Decomposition
MotionDreamer: One-to-Many Motion Synthesis with Localized Generative Masked Transformer
Learning Multi-Level Hierarchies with Hindsight
Separation and Concentration in Deep Networks
Boundary Denoising for Video Activity Localization
Compositional Obverter Communication Learning from Raw Visual Input
RIDE: Rewarding Impact-Driven Exploration for Procedurally-Generated Environments
Learning to Search from Demonstration Sequences
Revisiting Intrinsic Reward for Exploration in Procedurally Generated Environments
Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models
Efficient Evolutionary Search Over Chemical Space with Large Language Models
VA-DepthNet: A Variational Approach to Single Image Depth Prediction
Scale-Free Graph-Language Models
Text2Face: 3D Morphable Faces From Text
Predicting Physics in Mesh-reduced Space with Temporal Attention
Evaluating the Zero-shot Robustness of Instruction-tuned Language Models
On the Role of Discrete Tokenization in Visual Representation Learning
Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings
MoLEx: Mixture of Layer Experts for Fine-tuning with Sparse Upcycling
KnowDA: All-in-One Knowledge Mixture Model for Data Augmentation in Low-Resource NLP
From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation
Time-Varying Propensity Score to Bridge the Gap between the Past and Present
FractalNet: Ultra-Deep Neural Networks without Residuals
Weighted-Reward Preference Optimization for Implicit Model Fusion
Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection
GUI-World: A Video Benchmark and Dataset for Multimodal GUI-oriented Understanding
What Do Self-Supervised Vision Transformers Learn?
One-for-All Few-Shot Anomaly Detection via Instance-Induced Prompt Learning
Contrastive Learning of Structured World Models
Improved memory in recurrent neural networks with sequential non-normal dynamics
How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models
Dynamic Multimodal Evaluation with Flexible Complexity by Vision-Language Bootstrapping
Training Socially Aligned Language Models on Simulated Social Interactions
Does Zero-Shot Reinforcement Learning Exist?
Iterated learning for emergent systematicity in VQA
Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees
BAM: Bayes with Adaptive Memory
Scaling Autoregressive Video Models
Conformalized Survival Analysis for General Right-Censored Data
Distributed Fine-tuning of Language Models on Private Data
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective
Group-based Interleaved Pipeline Parallelism for Large-scale DNN Training
Effect of scale on catastrophic forgetting in neural networks
Pre-training with Random Orthogonal Projection Image Modeling
On Representation Complexity of Model-based and Model-free Reinforcement Learning
Learning interpretable control inputs and dynamics underlying animal locomotion
Adversarially Robust Representations with Smooth Encoders
Particle-based Variational Inference with Preconditioned Functional Gradient Flow
Beyond Autoregression: Fast LLMs via Self-Distillation Through Time
Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation
QA-Calibration of Language Model Confidence Scores
Understanding Influence Functions and Datamodels via Harmonic Analysis
Balancing Act: Diversity and Consistency in Large Language Model Ensembles
WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions
FluidLab: A Differentiable Environment for Benchmarking Complex Fluid Manipulation
Red PANDA: Disambiguating Image Anomaly Detection by Removing Nuisance Factors
Clean-image Backdoor: Attacking Multi-label Models with Poisoned Labels Only
DIVA: Dataset Derivative of a Learning Task
Overthinking the Truth: Understanding how Language Models Process False Demonstrations
Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks
Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects
Generalization Bounds for Canonicalization: A Comparative Study with Group Averaging
On Large Language Model Continual Unlearning
Magnitude Invariant Parametrizations Improve Hypernetwork Learning
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning
Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms
Global Convergence of Policy Gradient in Average Reward MDPs
Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI
Fast unsupervised ground metric learning with tree-Wasserstein distance
Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters
Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning
WorkflowLLM: Enhancing Workflow Orchestration Capability of Large Language Models
Towards a Deep Network Architecture for Structured Smoothness
Write and Paint: Generative Vision-Language Models are Unified Modal Learners
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning
Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis
Sampling-free Inference for Ab-Initio Potential Energy Surface Networks
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods
Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds
Approximate Vanishing Ideal Computations at Scale
LLM Augmented LLMs: Expanding Capabilities through Composition
Diffusion Generative Modeling for Spatially Resolved Gene Expression Inference from Histology Images
Planning from Pixels using Inverse Dynamics Models
Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach
CycleMLP: A MLP-like Architecture for Dense Prediction
Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification
Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Steps
CellPLM: Pre-training of Cell Language Model Beyond Single Cells
Link Prediction with Non-Contrastive Learning
The Laplacian in RL: Learning Representations with Efficient Approximations
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism
Truncated horizon Policy Search: Combining Reinforcement Learning & Imitation Learning
An Evaluation of Fisher Approximations Beyond Kronecker Factorization
Active Contrastive Learning of Audio-Visual Video Representations
Influence-Guided Diffusion for Dataset Distillation
Rethinking and Improving Autoformalization: Towards a Faithful Metric and a Dependency Retrieval-based Approach
Arithmetic Transformers Can Length-Generalize in Both Operand Length and Count
Finetuning Text-to-Image Diffusion Models for Fairness
Improving the Universality and Learnability of Neural Programmer-Interpreters with Combinator Abstraction
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems
Bayesian Regularization of Latent Representation
Online Coreset Selection for Rehearsal-based Continual Learning
ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing
Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem
Directional Gradient Projection for Robust Fine-Tuning of Foundation Models
Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling
INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving
Towards 3D Molecule-Text Interpretation in Language Models
TapMo: Shape-aware Motion Generation of Skeleton-free Characters
Context-Aware Sparse Deep Coordination Graphs
Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning
Attacking the Madry Defense Model with $L_1$-based Adversarial Examples
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
GeneDisco: A Benchmark for Experimental Design in Drug Discovery
Switch-NeRF: Learning Scene Decomposition with Mixture of Experts for Large-scale Neural Radiance Fields
Subsampling in Large Graphs Using Ricci Curvature
Scaling Laws for Adversarial Attacks on Language Model Activations and Tokens
Advancing LLM Reasoning Generalists with Preference Trees
Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders
Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning
Scenario-based Question Answering with Interacting Contextual Properties
On Identifiability in Transformers
Long-Context Linear System Identification
On the Critical Role of Conventions in Adaptive Human-AI Collaboration
TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations
Neural Language Modeling by Jointly Learning Syntax and Lexicon
The inductive bias of ReLU networks on orthogonally separable data
Exploring the Limits of Semantic Image Compression at Micro-bits per Pixel
SuperCorrect: Advancing Small LLM Reasoning with Thought Template Distillation and Self-Correction
Streaming Video Question-Answering with In-context Video KV-Cache Retrieval
Kernel RNN Learning (KeRNL)
Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?
PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling
A-Bench: Are LMMs Masters at Evaluating AI-generated Images?
GOAt: Explaining Graph Neural Networks via Graph Output Attribution
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design
Teach LLMs to Phish: Stealing Private Information from Language Models
Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression
CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning
Efficient Sharpness-aware Minimization for Improved Training of Neural Networks
Quantifying and Enhancing Multi-modal Robustness with Modality Preference
Modeling Sequential Sentence Relation to Improve Cross-lingual Dense Retrieval
Boosting the visual interpretability of CLIP via adversarial fine-tuning
Seeing Eye to AI: Human Alignment via Gaze-Based Response Rewards for Large Language Models
Amortised MAP Inference for Image Super-resolution
TorchTitan: One-stop PyTorch native solution for production ready LLM pretraining
VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models
ProteinBench: A Holistic Evaluation of Protein Foundation Models
Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies
Concept Understanding in Large Language Models: An Empirical Study
Improving Image Editing Models with Generative Data Refinement
Fictitious Synthetic Data Can Improve LLM Factuality via Prerequisite Learning
A General Analysis of Example-Selection for Stochastic Gradient Descent
Bit-Pruning: A Sparse Multiplication-Less Dot-Product
Rethinking and Extending the Probabilistic Inference Capacity of GNNs
Knowledge Consistency between Neural Networks and Beyond
Robustness Reprogramming for Representation Learning
GNNs Getting ComFy: Community and Feature Similarity Guided Rewiring
Rapid Task-Solving in Novel Environments
DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks
Promptagator: Few-shot Dense Retrieval From 8 Examples
A Cognitive Model for Learning Abstract Relational Structures from Memory-based Decision-Making Tasks
MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning
BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models
Language Models are Realistic Tabular Data Generators
Efficient Off-Policy Learning for High-Dimensional Action Spaces
Word translation without parallel data
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence
Cognitive resilience: Unraveling the proficiency of image-captioning models to interpret masked visual content
Training-free LLM-generated Text Detection by Mining Token Probability Sequences
Learning Conditional Invariances through Non-Commutativity
Accelerating Nonconvex Learning via Replica Exchange Langevin diffusion
KAN: Kolmogorov-Arnold Networks
INViTE: INterpret and Control Vision-Language Models with Text Explanations
Representation-Agnostic Shape Fields
Exploring Efficient and Simple Initialization Strategies for Bayesian Optimization with SETUP-BO
Can Transformers Do Enumerative Geometry?
No Spurious Local Minima in a Two Hidden Unit ReLU Network
Parameter and Memory Efficient Pretraining via Low-rank Riemannian Optimization
Optimization and Adaptive Generalization of Three layer Neural Networks
A Scalable Laplace Approximation for Neural Networks
Fast Training of Sinusoidal Neural Fields via Scaling Initialization
Learning Object-Language Alignments for Open-Vocabulary Object Detection
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
A Stochastic Derivative Free Optimization Method with Momentum
EventRPG: Event Data Augmentation with Relevance Propagation Guidance
First-Person Fairness in Chatbots
Kernel-based Optimally Weighted Conformal Time-Series Prediction
Fixed Non-negative Orthogonal Classifier: Inducing Zero-mean Neural Collapse with Feature Dimension Separation
DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile
CtrLoRA: An Extensible and Efficient Framework for Controllable Image Generation
Near-Optimal Adversarial Reinforcement Learning with Switching Costs
Language Models Need Inductive Biases to Count Inductively
Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping
HAINAN: Fast and Accurate Transducer for Hybrid-Autoregressive ASR
Efficient Masked AutoEncoder for Video Object Counting and A Large-Scale Benchmark
Can Reinforcement Learning Solve Asymmetric Combinatorial-Continuous Zero-Sum Games?
Zero-cost Proxy for Adversarial Robustness Evaluation
Human MotionFormer: Transferring Human Motions with Vision Transformers
Intrinsic Motivation for Encouraging Synergistic Behavior
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning
Tracking objects that change in appearance with phase synchrony
StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random
Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding
SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand Cores
Reward Uncertainty for Exploration in Preference-based Reinforcement Learning
GAT: Generative Adversarial Training for Adversarial Example Detection and Robust Classification
Balancing Bias in Two-sided Markets for Fair Stable Matchings
Monocular Scene Reconstruction with 3D SDF Transformers
Mind the GAP: Glimpse-based Active Perception improves generalization and sample efficiency of visual reasoning
Theta sequences as eligibility traces: A biological solution to credit assignment
Continual Momentum Filtering on Parameter Space for Online Test-time Adaptation
Surrogate Gap Minimization Improves Sharpness-Aware Training
Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages
Self-Teaching Prompting for Multi-Intent Learning with Limited Supervision
N2N learning: Network to Network Compression via Policy Gradient Reinforcement Learning
Query-Policy Misalignment in Preference-Based Reinforcement Learning
Words are all you need? Language as an approximation for human similarity judgments
Semantic Similarity Based Label Augmentation for Visual Classification
STREET: A Multi-Task Structured Reasoning and Explanation Benchmark
Long-tailed Adversarial Training with Self-Distillation
LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning
Computational Separation Between Convolutional and Fully-Connected Networks
Huber Additive Models for Non-stationary Time Series Analysis
Towards Building A Group-based Unsupervised Representation Disentanglement Framework
Learning to Represent Action Values as a Hypergraph on the Action Vertices
R-EDL: Relaxing Nonessential Settings of Evidential Deep Learning
Towards Scalable Topological Regularizers
Unhackable Temporal Reward for Scalable Video MLLMs
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals
Self-Supervised Inference in State-Space Models
The Recurrent Neural Tangent Kernel
One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models
What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
Analyzing and Improving Optimal-Transport-based Adversarial Networks
Agnostic Learning of General ReLU Activation Using Gradient Descent
Large-scale Training of Foundation Models for Wearable Biosignals
Coherent Gradients: An Approach to Understanding Generalization in Gradient Descent-based Optimization
Deconstructing Distributions: A Pointwise Framework of Learning
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets
Distance-Based Learning from Errors for Confidence Calibration
Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework
CodePlan: Unlocking Reasoning Potential in Large Language Models by Scaling Code-form Planning
Zero-Shot Self-Supervised Learning for MRI Reconstruction
Spiking Convolutional Neural Networks for Text Classification
FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Models