yusuke1997/dblp-id-title huggingface dataset:
You Only Train Once: Loss-Conditional Training of Deep Networks
Learning Towards The Largest Margins
Neural Polynomial Gabor Fields for Macro Motion Analysis
Backdoor Federated Learning by Poisoning Backdoor-Critical Layers
GenSim: Generating Robotic Simulation Tasks via Large Language Models
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments
Adaptive Robust Evidential Optimization For Open Set Detection from Imbalanced Data
Hindsight policy gradients
In Search of Lost Domain Generalization
Loopy: Taming Audio-Driven Portrait Avatar with Long-Term Motion Dependency
Minimal Impact ControlNet: Advancing Multi-ControlNet Integration
Prompting Fairness: Integrating Causality to Debias Large Language Models
SAM 2: Segment Anything in Images and Videos
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models
Let Me Grok for You: Accelerating Grokking via Embedding Transfer from a Weaker Model
Neural Processes with Stochastic Attention: Paying more attention to the context dataset
Dataset Augmentation in Feature Space
Horizon-Free Regret for Linear Markov Decision Processes
iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data
SGDR: Stochastic Gradient Descent with Warm Restarts
Mastering the Dungeon: Grounded Language Learning by Mechanical Turker Descent
Iterative Circuit Repair Against Formal Specifications
Aligned Better, Listen Better for Audio-Visual Large Language Models
Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations
Graph-Based Continual Learning
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference
Double Neural Counterfactual Regret Minimization
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
Learning Multi-Faceted Prototypical User Interests
How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation
ToolGen: Unified Tool Retrieval and Calling via Generation
Extreme Memorization via Scale of Initialization
Discrete Copula Diffusion
Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models
Round and Round We Go! What makes Rotary Positional Encodings useful?
Learning To Solve Circuit-SAT: An Unsupervised Differentiable Approach
Mapping Language Models to Grounded Conceptual Spaces
ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation
Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models
Learning ReLU networks to high uniform accuracy is intractable
DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image Generation
Rethinking Shapley Value for Negative Interactions in Non-convex Games
Walk the Talk? Measuring the Faithfulness of Large Language Model Explanations
SemiReward: A General Reward Model for Semi-supervised Learning
AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation
Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures
Learning Sparse and Low-Rank Priors for Image Recovery via Iterative Reweighted Least Squares Minimization
Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks
When Semantic Segmentation Meets Frequency Aliasing
Unveiling the sampling density in non-uniform geometric graphs
Become a Proficient Player with Limited Data through Watching Pure Videos
COSA: Concatenated Sample Pretrained Vision-Language Foundation Model
Relative representations enable zero-shot latent space communication
Plugin estimators for selective classification with out-of-distribution detection
TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting
Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models
Illiterate DALL-E Learns to Compose
MolSpectra: Pre-training 3D Molecular Representation with Multi-modal Energy Spectra
Deep Generative Models for Highly Structured Data, ICLR 2019 Workshop, New Orleans, Louisiana, United States, May 6, 2019
Interpreting Language Reward Models via Contrastive Explanations
Unify ML4TSP: Drawing Methodological Principles for TSP and Beyond from Streamlined Design Space of Learning and Search
Geometry-Aware Projective Mapping for Unbounded Neural Radiance Fields
IDArb: Intrinsic Decomposition for Arbitrary Number of Input Views and Illuminations
Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning
Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning
D2O: Dynamic Discriminative Operations for Efficient Long-Context Inference of Large Language Models
Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation
Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions
DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation
Diffusion Actor-Critic: Formulating Constrained Policy Iteration as Diffusion Noise Regression for Offline Reinforcement Learning
Kalman Filter for Online Classification of Non-Stationary Data
ADIFF: Explaining audio difference using natural language
Generalized rectifier wavelet covariance models for texture synthesis
Refining Deep Generative Models via Discriminator Gradient Flow
Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data
InfinityGAN: Towards Infinite-Pixel Image Synthesis
Distributed Distributional Deterministic Policy Gradients
Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion
vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations
Quantum (Inspired) D2-sampling with Applications
Serving Graph Compression for Graph Neural Networks
Population-Guided Parallel Policy Search for Reinforcement Learning
Boosting Graph Anomaly Detection with Adaptive Message Passing
Faithful Rule Extraction for Differentiable Rule Learning Models
Feature emergence via margin maximization: case studies in algebraic tasks
Group Downsampling with Equivariant Anti-aliasing
LLaMA-Adapter: Efficient Fine-tuning of Large Language Models with Zero-initialized Attention
Evaluation of Neural Architectures trained with square Loss vs Cross-Entropy in Classification Tasks
Hyper-SAGNN: a self-attention based graph neural network for hypergraphs
L-WISE: Boosting Human Visual Category Learning Through Model-Based Image Selection and Enhancement
Pre-training Tasks for Embedding-based Large-scale Retrieval
Dense Video Object Captioning from Disjoint Supervision
Exploring Balanced Feature Spaces for Representation Learning
Automatically Discovering and Learning New Visual Categories with Ranking Statistics
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks
Teaching Temporal Logics to Neural Networks
PGrad: Learning Principal Gradients For Domain Generalization
GPromptShield: Elevating Resilience in Graph Prompt Tuning Against Adversarial Attacks
What should a neuron aim for? Designing local objective functions based on information theory
Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach
Reproducibility in Machine Learning, ICLR 2019 Workshop, New Orleans, Louisiana, United States, May 6, 2019
InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning
A CLIP-Powered Framework for Robust and Generalizable Data Selection
Information-theoretic Online Memory Selection for Continual Learning
Pacmann: Efficient Private Approximate Nearest Neighbor Search
InstaSHAP: Interpretable Additive Models Explain Shapley Values Instantly
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking
Hyperbolic Genome Embeddings
Disentanglement of Correlated Factors via Hausdorff Factorized Support
Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective
POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition
Statistical Guarantees for Consensus Clustering
Routing Networks: Adaptive Selection of Non-Linear Functions for Multi-Task Learning
Light-MILPopt: Solving Large-scale Mixed Integer Linear Programs with Lightweight Optimizer and Small-scale Training Dataset
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD
How much Position Information Do Convolutional Neural Networks Encode?
Advancing Mathematical Reasoning in Language Models: The Impact of Problem-Solving Data, Data Synthesis Methods, and Training Stages
TVSPrune - Pruning Non-discriminative filters via Total Variation separability of intermediate representations without fine tuning
Prometheus: Inducing Fine-Grained Evaluation Capability in Language Models
CrAM: A Compression-Aware Minimizer
GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation
Decision Boundary Analysis of Adversarial Examples
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers
Autonomous Evaluation of LLMs for Truth Maintenance and Reasoning Tasks
The First Tiny Papers Track at ICLR 2023, Tiny Papers @ ICLR 2023, Kigali, Rwanda, May 5, 2023
RESfM: Robust Deep Equivariant Structure from Motion
Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics
Improving LoRA in Privacy-preserving Federated Learning
Explaining Point Processes by Learning Interpretable Temporal Logic Rules
Low-Resource Knowledge-Grounded Dialogue Generation
Refine-by-Align: Reference-Guided Artifacts Refinement through Semantic Alignment
Learnable Topological Features For Phylogenetic Inference via Graph Neural Networks
Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML
Ringing ReLUs: Harmonic Distortion Analysis of Nonlinear Feedforward Networks
Diffusion-TS: Interpretable Diffusion for General Time Series Generation
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Understanding Over-parameterization in Generative Adversarial Networks
GNN is a Counter? Revisiting GNN for Question Answering
8-bit Optimizers via Block-wise Quantization
Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning
Density estimation using Real NVP
Mixture of In-Context Prompters for Tabular PFNs
Do Deep Convolutional Nets Really Need to be Deep and Convolutional?
Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantification
What they do when in doubt: a study of inductive biases in seq2seq learners
Learning Localized Generative Models for 3D Point Clouds via Graph Convolution
Anti-Symmetric DGN: a stable architecture for Deep Graph Networks
Learning from Graphs Beyond Message Passing Neural Networks
Biologically Plausible Brain Graph Transformer
Towards Auto-Regressive Next-Token Prediction: In-context Learning Emerges from Generalization
Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions
Hybrid Directional Graph Neural Network for Molecules
How to Find the Exact Pareto Front for Multi-Objective MDPs?
Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency
Exploring Local Memorization in Diffusion Models via Bright Ending Attention
Context-adaptive Entropy Model for End-to-end Optimized Image Compression
On the mapping between Hopfield networks and Restricted Boltzmann Machines
Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach
Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards
Shape or Texture: Understanding Discriminative Features in CNNs
A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models
Grounding Language to Autonomously-Acquired Skills via Goal Generation
WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning
AutoQ: Automated Kernel-Wise Neural Network Quantization
3D generation on ImageNet
Invariant and Equivariant Graph Networks
Neural Language of Thought Models
Beyond Content Relevance: Evaluating Instruction Following in Retrieval Models
Deep Distributed Optimization for Large-Scale Quadratic Programming
Reasoning with Memory Augmented Neural Networks for Language Comprehension
How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs
Robust Weight Initialization for Tanh Neural Networks with Fixed Point Analysis
Measuring and regularizing networks in function space
What's New in My Data? Novelty Exploration via Contrastive Generation
AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs
Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning
AE-FLOW: Autoencoders with Normalizing Flows for Medical Images Anomaly Detection
Faster Gradient-Free Methods for Escaping Saddle Points
Universal Agent for Disentangling Environments and Tasks
Branch-GAN: Improving Text Generation with (not so) Large Language Models
Neural Solvers for Fast and Accurate Numerical Optimal Control
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space
Semialgebraic Neural Networks: From roots to representations
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes
Tangent Transformers for Composition, Privacy and Removal
signSGD with Majority Vote is Communication Efficient and Fault Tolerant
Decentralized Deep Learning with Arbitrary Communication Compression
Energy-Based Test Sample Adaptation for Domain Generalization
Coupled Ensembles of Neural Networks
Training invariances and the low-rank phenomenon: beyond linear networks
A Seed-Augment-Train Framework for Universal Digit Classification
Temporal Difference Variational Auto-Encoder
SimpleTM: A Simple Baseline for Multivariate Time Series Forecasting
VTDexManip: A Dataset and Benchmark for Visual-tactile Pretraining and Dexterous Manipulation with Reinforcement Learning
Query Efficient Decision Based Sparse Attacks Against Black-Box Deep Learning Models
Efficient Lifelong Learning with A-GEM
Optimal Transport for Long-Tailed Recognition with Learnable Cost Matrix
Mind the Pool: Convolutional Neural Networks Can Overfit Input Size
LongGenBench: Benchmarking Long-Form Generation in Long Context LLMs
Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent
On the Limitations of Temperature Scaling for Distributions with Overlaps
ReGen: Generative Robot Simulation via Inverse Design
Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency
Gap Preserving Distillation by Building Bidirectional Mappings with A Dynamic Teacher
Understanding Why Neural Networks Generalize Well Through GSNR of Parameters
$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks
Learning Multimodal Graph-to-Graph Translation for Molecule Optimization
$k$NN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference
NeuroLM: A Universal Multi-task Foundation Model for Bridging the Gap between Language and EEG Signals
SALMON: Self-Alignment with Instructable Reward Models
PolyPythias: Stability and Outliers across Fifty Language Model Pre-Training Runs
Data Valuation Without Training of a Model
Reconstructive Visual Instruction Tuning
TypedThinker: Diversify Large Language Model Reasoning with Typed Thinking
Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning
Learning Curves for SGD on Structured Features
Closed-Form Merging of Parameter-Efficient Modules for Federated Continual Learning
Vec2Face: Scaling Face Dataset Generation with Loosely Constrained Vectors
DEPT: Decoupled Embeddings for Pre-training Language Models
Interaction-Based Disentanglement of Entities for Object-Centric World Models
Stacking/Ensemble Model for Smartphone-Based Human Activity Recognition using Feature Engineering
Easing non-convex optimization with neural networks
Uncertainty-aware Graph-based Hyperspectral Image Classification
Can We Find Nash Equilibria at a Linear Rate in Markov Games?
Overcoming Catastrophic Forgetting for Continual Learning via Model Adaptation
SimXRD-4M: Big Simulated X-ray Diffraction Data and Crystal Symmetry Classification Benchmark
Transformers Learn Low Sensitivity Functions: Investigations and Implications
A Conditional Independence Test in the Presence of Discretization
HQ-Edit: A High-Quality Dataset for Instruction-based Image Editing
Warm Diffusion: Recipe for Blur-Noise Mixture Diffusion Models
CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models
Bregman Gradient Policy Optimization
Strong inductive biases provably prevent harmless interpolation
Learning via social awareness: improving sketch representations with facial feedback
Breaking the log⁡(1/Δ2) Barrier: Better Batched Best Arm Identification with Adaptive Grids
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling
FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning
Geom-GCN: Geometric Graph Convolutional Networks
Transformer-based model for symbolic regression via joint supervised learning
Human-Level Performance in No-Press Diplomacy via Equilibrium Search
Uncertainty-guided Continual Learning with Bayesian Neural Networks
Image-level Memorization Detection via Inversion-based Inference Perturbation
Variational Bayesian Phylogenetic Inference
From Pixels to Tokens: Byte-Pair Encoding on Quantized Visual Modalities
SimbaML: Connecting Mechanistic Models and Machine Learning with Augmented Data
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
EasyTPP: Towards Open Benchmarking Temporal Point Processes
Entropy-MCMC: Sampling from Flat Basins with Ease
Topic Modeling as Multi-Objective Contrastive Optimization
Adversarial Imitation via Variational Inverse Reinforcement Learning
mixup: Beyond Empirical Risk Minimization
Model Equality Testing: Which Model is this API Serving?
Limits of Deep Learning: Sequence Modeling through the Lens of Complexity Theory
Classification-Based Anomaly Detection for General Data
A Study on Polarity distributions for Network Learning
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction
End-to-end Adversarial Text-to-Speech
Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization
Entropy Coding of Unordered Data Structures
ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning
Model-Free Offline Reinforcement Learning with Enhanced Robustness
Synthesizing realistic neural population activity patterns using Generative Adversarial Networks
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks
Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets
Towards Addressing Label Skews in One-Shot Federated Learning
Demystifying the Token Dynamics of Deep Selective State Space Models
Prompt-to-Prompt Image Editing with Cross-Attention Control
Learning Heuristics for Quantified Boolean Formulas through Reinforcement Learning
AutoG: Towards automatic graph construction from tabular data
Scaling Supervised Local Learning with Augmented Auxiliary Networks
Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting
Learning Zero-Shot Cooperation with Humans, Assuming Humans Are Biased
Spectral Augmentation for Self-Supervised Learning on Graphs
Immunogenicity Prediction with Dual Attention Enables Vaccine Target Selection
OntoProtein: Protein Pretraining With Gene Ontology Embedding
Inductive and Unsupervised Representation Learning on Graph Structured Objects
Robustness Evaluation of Multi-Agent Reinforcement Learning Algorithms using GNAs
StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning
Guiding Program Synthesis by Learning to Generate Examples
Relax and Merge: A Simple Yet Effective Framework for Solving Fair k-Means and k-sparse Wasserstein Barycenter Problems
Longhorn: State Space Models are Amortized Online Learners
Lipschitz Bandits in Optimal Space
Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace
Leveraging Automated Unit Tests for Unsupervised Code Translation
Quantitatively Evaluating GANs With Divergences Proposed for Training
Reasoning with Latent Thoughts: On the Power of Looped Transformers
Distributed Extra-gradient with Optimal Complexity and Communication Guarantees
Understanding the Variance Collapse of SVGD in High Dimensions
Optimal transport based adversarial patch to leverage large scale attack transferability
Discerning Self-supervised Learning and Weakly Supervised Learning
An Operator Theoretic View On Pruning Deep Neural Networks
SOInter: A Novel Deep Energy-Based Interpretation Method for Explaining Structured Output Models
Regularized Offline GFlowNets
Detecting Egregious Responses in Neural Sequence-to-sequence Models
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
STCN: Stochastic Temporal Convolutional Networks
Robustifying and Boosting Training-Free Neural Architecture Search
Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization
Projection-Based Constrained Policy Optimization
Efficient and Robust Neural Combinatorial Optimization via Wasserstein-Based Coresets
Continuous Diffusion for Mixed-Type Tabular Data
Non Parametric Aleatoric Uncertainty Quantification with Neural Networks
Beyond single neurons: population response geometry in digital twins of mouse visual cortex
PC2WF: 3D Wireframe Reconstruction from Raw Point Clouds
GOGGLE: Generative Modelling for Tabular Data by Learning Relational Structure
Conformation-Guided Molecular Representation with Hamiltonian Neural Networks
AD-VAT: An Asymmetric Dueling mechanism for learning Visual Active Tracking
ACES: Automatic Cohort Extraction System for Event-Stream Datasets
Fair Attribute Completion on Graph with Missing Attributes
FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy
Separate and Diffuse: Using a Pretrained Diffusion Model for Better Source Separation
Circuit Representation Learning with Masked Gate Modeling and Verilog-AIG Alignment
Learning to Reason with Autoregressive In-Context Distillation
Efficient and Scalable Graph Generation through Iterative Local Expansion
HYPO: Hyperspherical Out-Of-Distribution Generalization
Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer
FOSI: Hybrid First and Second Order Optimization
Neural Stochastic Dual Dynamic Programming
Amulet: ReAlignment During Test Time for Personalized Preference Adaptation of LLMs
Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online
Variational Autoencoder with Arbitrary Conditioning
Resource-efficient image inpainting
Robust early-learning: Hindering the memorization of noisy labels
Efficient Probabilistic Logic Reasoning with Graph Neural Networks
Bringing NeRFs to the Latent Space: Inverse Graphics Autoencoder
Online Continual Learning for Interactive Instruction Following Agents
Learning an Embedding Space for Transferable Robot Skills
Variational autoencoders trained with q-deformed lower bounds
Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data
Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials
Revisiting Robustness in Graph Machine Learning
The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning