yusuke1997/dblp-id-title huggingface dataset:
Rethinking the generalization of drug target affinity prediction algorithms via similarity aware evaluation
Generalizable Features From Unsupervised Learning
Neural Execution of Graph Algorithms
Ensemble Adversarial Training: Attacks and Defenses
Palmbench: a comprehensive Benchmark of Compressed Large Language Models on Mobile Platforms
Predictive Inference with Feature Conformal Prediction
Quantized Spike-driven Transformer
Pruning Deep Neural Networks from a Sparsity Perspective
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting
MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting
Adaptive Federated Learning with Auto-Tuned Clients
Functional variational Bayesian Neural Networks
Inverse Rendering using Multi-Bounce Path Tracing and Reservoir Sampling
Structural Fairness-aware Active Learning for Graph Neural Networks
Task-Agnostic Morphology Evolution
Diffusion State-Guided Projected Gradient for Inverse Problems
Hierarchical Density Order Embeddings
Unsupervised Model Selection for Variational Disentangled Representation Learning
Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory
In reinforcement learning, all objective functions are not equal
Steerable CNNs
Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model
Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval
Backpropagation through the Void: Optimizing control variates for black-box gradient estimation
Counterfactual Generative Networks
Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialogues
Generative Human Motion Stylization in Latent Space
Training Compressed Fully-Connected Networks with a Density-Diversity Penalty
Model-augmented Prioritized Experience Replay
Single Motion Diffusion
Adaptive Dropout with Rademacher Complexity Regularization
Planning Goals for Exploration
Is Adversarial Training Really a Silver Bullet for Mitigating Data Poisoning?
Predictive, scalable and interpretable knowledge tracing on structured domains
Decoding Game: On Minimax Optimality of Heuristic Text Generation Strategies
Conditioning Sequence-to-sequence Networks with Learned Activations
Learning Iterative Neural Optimizers for Image Steganography
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach
Accurate and Scalable Graph Neural Networks via Message Invariance
Lines of Thought in Large Language Models
Improving Uncertainty Estimation through Semantically Diverse Language Generation
SAM-CP: Marrying SAM with Composable Prompts for Versatile Segmentation
Network Augmentation for Tiny Deep Learning
How do Language Models Bind Entities in Context?
Preferences Implicit in the State of the World
AI-based opportunistic analysis of the CT images during COVID (2021): Does living in a metropolitan area affect the vertebral body mineral density in older people?
ONLS: Optimal Noise Level Search in Diffusion Autoencoders Without Fine-Tuning
TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting
Generalized Demographic Parity for Group Fairness
Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis
AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents
Idempotence and Perceptual Image Compression
Image Background Serves as Good Proxy for Out-of-distribution Data
AvatarGO: Zero-shot 4D Human-Object Interaction Generation and Animation
Think Thrice Before You Act: Progressive Thought Refinement in Large Language Models
Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation
Extreme Tensoring for Low-Memory Preconditioning
CoBIT: A Contrastive Bi-directional Image-Text Generation Model
Quantitative Performance Assessment of CNN Units via Topological Entropy Calculation
Critical initialisation in continuous approximations of binary neural networks
Towards Specification-Directed Program Repair
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability
Geometry-aware RL for Manipulation of Varying Shapes and Deformable Objects
Equal Improvability: A New Fairness Notion Considering the Long-term Impact
Endless Jailbreaks with Bijection Learning
On the Limitations of Multimodal VAEs
Wisdom of Committees: An Overlooked Approach To Faster and More Accurate Models
Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation
RECOMP: Improving Retrieval-Augmented LMs with Context Compression and Selective Augmentation
Bayes classifier cannot be learned from noisy responses with unknown noise rates
Towards Smooth Video Composition
Equivariance-aware Architectural Optimization of Neural Networks
HiCLIP: Contrastive Language-Image Pretraining with Hierarchy-aware Attention
PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation
Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation
Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data
Curriculum-aware Training for Discriminating Molecular Property Prediction Models
Capturing Structural Locality in Non-parametric Language Models
How connectivity structure shapes rich and lazy learning in neural circuits
NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation
Group Equivariant Stand-Alone Self-Attention For Vision
Adaptive Structural Fingerprints for Graph Attention Networks
Chemical Language Models Have Problems with Chemistry: A Case Study on Molecule Captioning Task
RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph
Towards Empirical Sandwich Bounds on the Rate-Distortion Function
Evaluating Robustness of Neural Networks with Mixed Integer Programming
Concept Bottleneck Large Language Models
DORA The Explorer: Directed Outreaching Reinforcement Action-Selection
MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
On Differentially Private Federated Linear Contextual Bandits
Model Extraction Attacks on DistilBERT
Learning through Dialogue Interactions by Asking Questions
TabCaps: A Capsule Neural Network for Tabular Data Classification with BoW Routing
Task Descriptors Help Transformers Learn Linear Models In-Context
On the Byzantine-Resilience of Distillation-Based Federated Learning
Discerning Self-Supervised Learning and Weakly Supervised Learning
Diversity-Rewarded CFG Distillation
Energy-based Automated Model Evaluation
OmnixR: Evaluating Omni-modality Language Models on Reasoning across Modalities
Optimal criterion for feature learning of two-layer linear neural network in high dimensional interpolation regime
SaMer: A Scenario-aware Multi-dimensional Evaluator for Large Language Models
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
Mitigating Emergent Robustness Degradation while Scaling Graph Learning
Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness
A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis
Interpretable Counting for Visual Question Answering
MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy
Axiomatic Explanations for Visual Search, Retrieval, and Similarity Learning
CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets
Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain
Dynamic Low-Rank Sparse Adaptation for Large Language Models
Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis
Combining Symbolic Expressions and Black-box Function Evaluations in Neural Programs
Wavelet Diffusion Neural Operator
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals
InstaGAN: Instance-aware Image-to-Image Translation
Learning dynamic representations of the functional connectome in neurobiological networks
Learning Strides in Convolutional Neural Networks
Autoregressive Pretraining with Mamba in Vision
Know Thyself: Transferable Visual Control Policies Through Robot-Awareness
Making RL with Preference-based Feedback Efficient via Randomization
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction
Memorization Precedes Generation: Learning Unsupervised GANs with Memory Networks
Tracing Representation Progression: Analyzing and Enhancing Layer-Wise Similarity
Igeood: An Information Geometry Approach to Out-of-Distribution Detection
On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality
TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks
Tilted Empirical Risk Minimization
Data Pruning by Information Maximization
Adversarial Training and Provable Defenses: Bridging the Gap
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel
Generalizable Adversarial Training via Spectral Normalization
Decision S4: Efficient Sequence-Based RL via State Spaces Layers
Training Mixture-of-Experts: A Focus on Expert-Token Matching
Analysis of Quantized Models
Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game
A General Framework for Producing Interpretable Semantic Text Embeddings
The Effectiveness of Curvature-Based Rewiring and the Role of Hyperparameters in GNNs Revisited
Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation
Gradient Step Denoiser for convergent Plug-and-Play
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
Privately Counting Partially Ordered Data
Graph Wavelet Neural Network
Information Geometry of Orthogonal Initializations and Training
Dataset Condensation with Gradient Matching
Maximum Entropy Model Correction in Reinforcement Learning
Retri3D: 3D Neural Graphics Representation Retrieval
Reconstructing evolutionary trajectories of mutations in cancer
Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data
Formation of Representations in Neural Networks
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes
Non-Exchangeable Conformal Risk Control
Augmented Cyclic Adversarial Learning for Low Resource Domain Adaptation
Memory Replay with Data Compression for Continual Learning
Harnessing Out-Of-Distribution Examples via Augmenting Content and Style
The Symmetric Generalized Eigenvalue Problem as a Nash Equilibrium
Understanding the Covariance Structure of Convolutional Filters
Influence Functions in Deep Learning Are Fragile
Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models
Gated Multimodal Units for Information Fusion
TypeT5: Seq2seq Type Inference using Static Analysis
Neural-based classification rule learning for sequential data
SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG
Characterizing Audio Adversarial Examples Using Temporal Dependency
Latent Convolutional Models
MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversations
Efficient Discovery of Pareto Front for Multi-Objective Reinforcement Learning
EViT: Expediting Vision Transformers via Token Reorganizations
Learning Dynamics of Deep Matrix Factorization Beyond the Edge of Stability
Minimum Description Length Control
Phase Collapse in Neural Networks
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
Learning Fast and Slow for Online Time Series Forecasting
You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning
CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs
Graph HyperNetworks for Neural Architecture Search
Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity
Learning a neural response metric for retinal prosthesis
MagicDrive: Street View Generation with Diverse 3D Geometry Control
Learning to Discover Regulatory Elements for Gene Expression Prediction
Improving Reasoning Performance in Large Language Models via Representation Engineering
Directed Acyclic Graph Neural Networks
Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation
Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs
A Statistical Approach to Assessing Neural Network Robustness
ROCO: A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs
Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments
Scale-Adaptive Diffusion Model for Complex Sketch Synthesis
Dysca: A Dynamic and Scalable Benchmark for Evaluating Perception Ability of LVLMs
How to Fine-Tune Vision Models with SGD
LLM-grounded Video Diffusion Models
A Design Space Study for LISTA and Beyond
Humanly Certifying Superhuman Classifiers
Variational Inference for Discriminative Learning with Generative Modeling of Feature Incompletion
MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context Generation with Speculative Decoding
When Graph Neural Networks Meet Dynamic Mode Decomposition
Online and stochastic optimization beyond Lipschitz continuity: A Riemannian approach
VoltaVision: A Transfer Learning model for electronic component classification
Competitive Physics Informed Networks
Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains
Learning View-invariant World Models for Visual Robotic Manipulation
WaNet - Imperceptible Warping-based Backdoor Attack
Measure the Predictive Heterogeneity
Collaborative Discrete-Continuous Black-Box Prompt Learning for Language Models
ShortcutsBench: A Large-Scale Real-world Benchmark for API-based Agents
A Baseline for Few-Shot Image Classification
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel
Efficient Jailbreak Attack sequences on Large Language Models via Multi-Armed Bandit-based Context switching
Learning Neurosymbolic Generative Models via Program synthesis
On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Multi-resolution modeling of a discrete stochastic process identifies causes of cancer
Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation
Variable Computation in Recurrent Neural Networks
On Rollouts in Model-Based Reinforcement Learning
Symmetric Pruning in Quantum Neural Networks
TaskGalaxy: Scaling Multi-modal Instruction Fine-tuning with Tens of Thousands Vision Task Types
SSLAM: Enhancing Self-Supervised Models with Audio Mixtures for Polyphonic Soundscapes
Difference-Seeking Generative Adversarial Network-Unseen Sample Generation
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
DeCap: Decoding CLIP Latents for Zero-Shot Captioning via Text-Only Training
Scaling FP8 training to trillion-token LLMs
Boosting the Certified Robustness of L-infinity Distance Nets
Leveraging Large Language Models for Multiple Choice Question Answering
Learning to Reject with a Fixed Predictor: Application to Decontextualization
Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization
Optimal Brain Apoptosis
YOLO-RD: Introducing Relevant and Compact Explicit Knowledge to YOLO by Retriever-Dictionary
An improved analysis of per-sample and per-update clipping in federated learning
Discovering and Explaining the Representation Bottleneck of DNNS
Watch the Unobserved: A Simple Approach to Parallelizing Monte Carlo Tree Search
Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis
Coeditor: Leveraging Repo-level Diffs for Code Auto-editing
Filtered Inner Product Projection for Crosslingual Embedding Alignment
Pl@ntNet app in the era of deep learning
Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse
Phase2vec: dynamical systems embedding with a physics-informed convolutional network
SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation
Disentangled Recurrent Wasserstein Autoencoder
Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models
Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems
BlueSuffix: Reinforced Blue Teaming for Vision-Language Models Against Jailbreak Attacks
Knowledge Infused Decoding
PPT: Patch Order Do Matters In Time Series Pretext Task
Masked Temporal Interpolation Diffusion for Procedure Planning in Instructional Videos
Anisotropic Message Passing: Graph Neural Networks with Directional and Long-Range Interactions
NerveNet: Learning Structured Policy with Graph Neural Networks
Minimal Variance Model Aggregation: A principled, non-intrusive, and versatile integration of black box models
Improving Sequence-to-Sequence Learning via Optimal Transport
Adaptive Energy Alignment for Accelerating Test-Time Adaptation
RNNs implicitly implement tensor-product representations
The Unusual Effectiveness of Averaging in GAN Training
Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learning
Improved Techniques for Training Consistency Models
Efficient and Differentiable Conformal Prediction with General Function Classes
Accurate Image Restoration with Attention Retractable Transformer
Smoothing the Shift: Towards Stable Test-Time Adaptation under Complex Multimodal Noises
Making Pre-trained Language Models Great on Tabular Prediction
Fast Updating Truncated SVD for Representation Learning with Sparse Matrices
TabWak: A Watermark for Tabular Diffusion Models
Novelty Detection Via Blurring
Cauchy-Schwarz Regularizers
Selective Aggregation for Low-Rank Adaptation in Federated Learning
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
SpaCE: The Spatial Confounding Environment
Trace Norm Regularised Deep Multi-Task Learning
Auto-scaling Vision Transformers without Training
Regularized Autoencoders for Isometric Representation Learning
BadJudge: Backdoor Vulnerabilities of LLM-As-A-Judge
Attributing Culture-Conditioned Generations to Pretraining Corpora
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks
Temporally-Extended ε-Greedy Exploration
DocPrompting: Generating Code by Retrieving the Docs
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions
Semi-Supervised Classification with Graph Convolutional Networks
Efficient Attention via Control Variates
FFJORD: Free-Form Continuous Dynamics for Scalable Reversible Generative Models
Reinforcement Learning in Presence of Discrete Markovian Context Evolution
MIND over Body: Adaptive Thinking using Dynamic Computation
Learning a subspace of policies for online adaptation in Reinforcement Learning
Don't Judge by the Look: Towards Motion Coherent Video Representation
Differentially Private Fractional Frequency Moments Estimation with Polylogarithmic Space
Learning with Feature-Dependent Label Noise: A Progressive Approach
A unifying view on implicit bias in training linear neural networks
3D Shape Completion via Sparse Irregular Representation
PerturboLLaVA: Reducing Multimodal Hallucinations with Perturbative Visual Training
RepFair-GAN: Mitigating Representation Bias in GANs Using Gradient Clipping
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models
Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories
Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text Guidance
RTFM: Generalising to New Environment Dynamics via Reading
Reinforcement Learning with Random Delays
Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation
The Hidden Convex Optimization Landscape of Regularized Two-Layer ReLU Networks: an Exact Characterization of Optimal Solutions
GANs Can Play Lottery Tickets Too
Towards Principled Methods for Training Generative Adversarial Networks
Generalizing Weisfeiler-Lehman Kernels to Subgraphs
Occlusion-aware Non-Rigid Point Cloud Registration via Unsupervised Neural Deformation Correntropy
Language Representations Can be What Recommenders Need: Findings and Potentials
Few-Shot Detection of Machine-Generated Text using Style Representations
Towards Neural Phrase-based Machine Translation
Unleashing the Power of Task-Specific Directions in Parameter Efficient Fine-tuning
1st International Conference on Learning Representations, ICLR 2013, Scottsdale, Arizona, USA, May 2-4, 2013, Workshop Track Proceedings
Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach
MosquitoFusion: A Multiclass Dataset for Real-Time Detection of Mosquitoes, Swarms, and Breeding Sites Using Deep Learning
Linear Log-Normal Attention with Unbiased Concentration
A Latent Morphology Model for Open-Vocabulary Neural Machine Translation
GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models
Spherical Tree-Sliced Wasserstein Distance
Protein Language Model Fitness is a Matter of Preference
SWIFT: On-the-Fly Self-Speculative Decoding for LLM Inference Acceleration
Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
UniRestore3D: A Scalable Framework For General Shape Restoration
Personalized Federated Learning with Feature Alignment and Classifier Collaboration
Debiasing Federated Learning with Correlated Client Participation
Manifold Preserving Guided Diffusion
Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning
COLLIE: Systematic Construction of Constrained Text Generation Tasks
Compositional Attention: Disentangling Search and Retrieval
Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering
Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval
Evaluating Representation Learning on the Protein Structure Universe
MemCNN: a Framework for Developing Memory Efficient Deep Invertible Networks
On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis
MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
GROOT: Learning to Follow Instructions by Watching Gameplay Videos
Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem
Stable Anisotropic Regularization
Interactive Visual Exploration of Latent Space (IVELS) for peptide auto-encoder model selection
Neural network gradient-based learning of black-box function interfaces
Efficiently Parameterized Neural Metriplectic Systems
Deterministic training of generative autoencoders using invertible layers
Proximal Mapping Loss: Understanding Loss Functions in Crowd Counting & Localization
Grokking as the transition from lazy to rich training dynamics
Linking Emergent and Natural Languages via Corpus Transfer
Decentralized Attribution of Generative Models
VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning
Exploring Learning Complexity for Efficient Downstream Dataset Pruning
Neural Methods for Logical Reasoning over Knowledge Graphs
MAPS: Advancing Multi-Modal Reasoning in Expert-Level Physical Science
Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness
Provable Learning-based Algorithm For Sparse Recovery
Learning Diffusion Bridges on Constrained Domains
When Biology has Chemistry: Solubility And Drug Subcategory Prediction using SMILES Strings
Efficient Token Mixing for Transformers via Adaptive Fourier Neural Operators