yusuke1997/dblp-id-title huggingface dataset:
Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation
Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks
Gromov-Wasserstein Autoencoders
Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens
A fast and accurate splitting method for optimal transport: analysis and implementation
Brain Bandit: A Biologically Grounded Neural Network for Efficient Control of Exploration
IPDreamer: Appearance-Controllable 3D Object Generation with Complex Image Prompts
Combating Adversarial Attacks Using Sparse Representations
Triangle and Four Cycle Counting with Predictions in Graph Streams
TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts
SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters
Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN
Policy improvement by planning with Gumbel
Amortized Network Intervention to Steer the Excitatory Point Processes
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning
Federated Granger Causality Learning For Interdependent Clients With State Space Representation
Semantic Re-tuning with Contrastive Tension
Better Generative Replay for Continual Federated Learning
Debiasing Concept-based Explanations with Causal Analysis
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
The Break-Even Point on Optimization Trajectories of Deep Neural Networks
Consistent Multi-Class Classification from Multiple Unlabeled Datasets
Rethinking Adversarial Transferability from a Data Distribution Perspective
Feedback Schrödinger Bridge Matching
What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study
How to Evaluate Reward Models for RLHF
Path Choice Matters for Clear Attributions in Path Methods
A Framework for Inference Inspired by Human Memory Mechanisms
Learning State Representations via Retracing in Reinforcement Learning
REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes
Ensembling Diffusion Models via Adaptive Feature Aggregation
EVC: Towards Real-Time Neural Image Compression with Mask Decay
Augmenting Non-Collaborative Dialog Systems with Explicit Semantic and Strategic Dialog History
Relational Forward Models for Multi-Agent Learning
Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization
Transformer-based Transform Coding
Bootstrapped Model Predictive Control
Pivot Pre-finetuning for Low Resource MT: A Case Study in Kikamba
Prevalence of Negative Transfer in Continual Reinforcement Learning: Analyses and a Simple Baseline
Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
Exploring Temporally Dynamic Data Augmentation for Video Recognition
FreeVS: Generative View Synthesis on Free Driving Trajectory
Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference
Refine Knowledge of Large Language Models via Adaptive Contrastive Learning
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
Structural-Entropy-Based Sample Selection for Efficient and Effective Learning
Data Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series
Dense RGB Slam with Neural Implicit Maps
Certified Defenses for Adversarial Patches
Path Auxiliary Proposal for MCMC in Discrete Space
Optimal Activation Functions for the Random Features Regression Model
UniCO: On Unified Combinatorial Optimization via Problem Reduction to Matrix-Encoded General TSP
Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis
FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis
Slimmable Neural Networks
Self-Boosting Large Language Models with Synthetic Preference Data
Conditional Image Generation by Conditioning Variational Auto-Encoders
No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks
DeepTAGE: Deep Temporal-Aligned Gradient Enhancement for Optimizing Spiking Neural Networks
Logicbreaks: A Framework for Understanding Subversion of Rule-based Inference
Learning Invariance with Compact Transforms
A closer look at the approximation capabilities of neural networks
Optimal Transport for Causal Discovery
Temperature Schedules for self-supervised contrastive methods on long-tail data
Initialized Equilibrium Propagation for Backprop-Free Training
Bayesian Optimization via Continual Variational Last Layer Training
Learning to Reach Goals via Iterated Supervised Learning
DocMIA: Document-Level Membership Inference Attacks against DocVQA Models
Model Agnostic Interpretability for Multiple Instance Learning
DRoC: Elevating Large Language Models for Complex Vehicle Routing via Decomposed Retrieval of Constraints
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions
End to End Trainable Active Contours via Differentiable Rendering
Solving Compositional Reinforcement Learning Problems via Task Reduction
PIED: Physics-Informed Experimental Design for Inverse Problems
Self-Supervised Learning of Compressed Video Representations
Parsing neural dynamics with infinite recurrent switching linear dynamical systems
Uncertainty in Gradient Boosting via Ensembles
Learning topology-preserving data representations
On the Perils of Cascading Robust Classifiers
How Many OptiFaces? A New Evaluation Metric For 3D Face Reconstruction
Autoencoding Variational Inference For Topic Models
Safe and Robust Watermark Injection with a Single OoD Image
LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked
Agent Skill Acquisition for Large Language Models via CycleQD
Tight Clusters Make Specialized Experts
Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models
Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task
LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment
Contextual Dropout: An Efficient Sample-Dependent Dropout Module
TEASER: Token Enhanced Spatial Modeling for Expressions Reconstruction
Needle In A Video Haystack: A Scalable Synthetic Evaluator for Video MLLMs
Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach
Adaptive Feature Abstraction for Translating Video to Language
LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory
Behavior Prior Representation learning for Offline Reinforcement Learning
X-NeMo: Expressive Neural Motion Reenactment via Disentangled Latent Attention
Faster Diffusion Sampling with Randomized Midpoints: Sequential and Parallel
Accurate Neural Training with 4-bit Matrix Multiplications at Standard Formats
Visualizing Information Conservation and Decomposition via the Information Matrix
Visual-O1: Understanding Ambiguous Instructions via Multi-modal Multi-turn Chain-of-thoughts Reasoning
Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost
HelpSteer2-Preference: Complementing Ratings with Preferences
Kinetix: Investigating the Training of General Agents through Open-Ended Physics-Based Control Tasks
Stochastic AUC Maximization with Deep Neural Networks
InstaTrain: Adaptive Training via Ultra-Fast Natural Annealing within Dynamical Systems
econSG: Efficient and Multi-view Consistent Open-Vocabulary 3D Semantic Gaussians
Meta Discovery: Learning to Discover Novel Classes given Very Limited Data
A3D: Does Diffusion Dream about 3D Alignment?
SRSA: Skill Retrieval and Adaptation for Robotic Assembly Tasks
Attacking deep networks with surrogate-based adversarial black-box methods is easy
How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data
RTDiff: Reverse Trajectory Synthesis via Diffusion for Offline Reinforcement Learning
From an LLM Swarm to a PDDL-empowered Hive: Planning Self-executed Instructions in a Multi-modal Jungle
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models
Asymptotic Instance-Optimal Algorithms for Interactive Decision Making
Adversarially Robust Out-of-Distribution Detection Using Lyapunov-Stabilized Embeddings
Learned Reference-based Diffusion Sampler for multi-modal distributions
Memorization-Dilation: Modeling Neural Collapse Under Noise
Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling
Learning Guarantees for Graph Convolutional Networks on the Stochastic Block Model
Parametric Augmentation for Time Series Contrastive Learning
A Coefficient Makes SVRG Effective
Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning
Neuromechanical Autoencoders: Learning to Couple Elastic and Neural Network Nonlinearity
Learning Long-Term Reward Redistribution via Randomized Return Decomposition
The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World
A Differentiable Rank-Based Objective for Better Feature Learning
More Experts Than Galaxies: Conditionally-Overlapping Experts with Biologically-Inspired Fixed Routing
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models
Long-horizon Visual Instruction Generation with Logic and Attribute Self-reflection
Fast topological clustering with Wasserstein distance
How Much Space Has Been Explored? Measuring the Chemical Space Covered by Databases and Machine-Generated Molecules
NeRF-SOS: Any-View Self-supervised Object Segmentation on Complex Scenes
Breaking Certified Defenses: Semantic Adversarial Examples with Spoofed robustness Certificates
Robust Angular Synchronization via Directed Graph Neural Networks
Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision
Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks
Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models
Hierarchical Visuomotor Control of Humanoids
Learning to Make Adherence-aware Advice
Deep Symbolic Superoptimization Without Human Knowledge
Efficient recurrent architectures through activity sparsity and sparse back-propagation through time
ACE: All-round Creator and Editor Following Instructions via Diffusion Transformer
MiniLLM: Knowledge Distillation of Large Language Models
Cross-Lingual Ability of Multilingual BERT: An Empirical Study
Meta-Learning with Warped Gradient Descent
Train Monolingual, Infer Bilingual
Retrieval-based Disentangled Representation Learning with Natural Language Supervision
Deep Point Cloud Reconstruction
ResNet After All: Neural ODEs and Their Numerical Solution
Automatic Functional Differentiation in JAX
Distribution-Interpolation Trade off in Generative Models
Scaling up the Banded Matrix Factorization Mechanism for Large Scale Differentially Private ML
A Generalized Semiconductor Wafer Defect Classifier
Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks
Do You Keep an Eye on What I Ask? Mitigating Multimodal Hallucination via Attention-Guided Ensemble Decoding
Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning
A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications
Certifying Counterfactual Bias in LLMs
Estimating individual treatment effects under unobserved confounding using binary instruments
OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models
Mini-batch k-means terminates within O(d/ϵ) iterations
Augmented Sliced Wasserstein Distances
Learning Structured Representations by Embedding Class Hierarchy
A Fair Comparison of Graph Neural Networks for Graph Classification
Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models
Graphon based Clustering and Testing of Networks: Algorithms and Theory
Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport
Learning to Learn with Conditional Class Dependencies
Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering
Fairness Guarantees under Demographic Shift
Iterated Reasoning with Mutual Information in Cooperative and Byzantine Decentralized Teaming
Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator
Multi-resolution HuBERT: Multi-resolution Speech Self-Supervised Learning with Masked Unit Prediction
SGD Converges to Global Minimum in Deep Learning via Star-convex Path
Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension
Learning Vision-Guided Quadrupedal Locomotion End-to-End with Cross-Modal Transformers
When narrower is better: the narrow width limit of Bayesian parallel branching neural networks
GANDALF: Generative AttentioN based Data Augmentation and predictive modeLing Framework for personalized cancer treatment
3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Workshop Track Proceedings
The loss surface and expressivity of deep convolutional neural networks
Multi-Task Processes
Permutation Compressors for Provably Faster Distributed Nonconvex Optimization
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Learning Probabilistic Topological Representations Using Discrete Morse Theory
Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification
Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting
Enhancing Language Model Agents using Diversity of Thoughts
GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction
Protein Representation Learning by Geometric Structure Pretraining
User Modeling Challenges in Interactive AI Assistant Systems
Hierarchical Autoregressive Transformers: Combining Byte- and Word-Level Processing for Robust, Adaptable Language Models
ViDT: An Efficient and Effective Fully Transformer-based Object Detector
The Crucial Role of Samplers in Online Direct Preference Optimization
Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms
h-detach: Modifying the LSTM Gradient Towards Better Optimization
Lipschitz-constrained Unsupervised Skill Discovery
GIM: Learning Generalizable Image Matcher From Internet Videos
An Undetectable Watermark for Generative Image Models
Proposal-Contrastive Pretraining for Object Detection from Fewer Data
A new framework for evaluating model out-of-distribution generalisation for the biochemical domain
Solving Continuous Control via Q-learning
Progressive Skeletonization: Trimming more fat from a network at initialization
Deep Learning 3D Shapes Using Alt-az Anisotropic 2-Sphere Convolution
GrabS: Generative Embodied Agent for 3D Object Segmentation without Scene Supervision
CoBERL: Contrastive BERT for Reinforcement Learning
Robust Explanation Constraints for Neural Networks
Improved Sampling Of Diffusion Models In Fluid Dynamics With Tweedie's Formula
Neural Processing of Tri-Plane Hybrid Neural Fields
Semantix: An Energy-guided Sampler for Semantic Style Transfer
Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs
Controlling Vision-Language Models for Multi-Task Image Restoration
Understanding Virtual Nodes: Oversquashing and Node Heterogeneity
On the role of planning in model-based deep reinforcement learning
Unbiased Supervised Contrastive Learning
SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement
Deep Equals Shallow for ReLU Networks in Kernel Regimes
Transfer Learning on Kinyarwanda Tweets Sentiment Analysis
Dynamic Assortment Selection and Pricing with Censored Preference Feedback
Unsupervised Domain Adaptation for Distance Metric Learning
Gyrogroup Batch Normalization
Disentanglement with Biological Constraints: A Theory of Functional Cell Types
OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
Text-Based Games as a Challenging Benchmark for Large Language Models
Session-Aware Product filter Ranking in E- Commerce Search
On the Universal Approximability and Complexity Bounds of Quantized ReLU Neural Networks
Rethinking Evaluation of Sparse Autoencoders through the Representation of Polysemous Words
From Inference to Generation: End-to-end Fully Self-supervised Generation of Human Face from Speech
GraphArena: Evaluating and Exploring Large Language Models on Graph Computation
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model
Model-Ensemble Trust-Region Policy Optimization
Mutual Partial Label Learning with Competitive Label Noise
BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization
Fair Normalizing Flows
A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model
Hyperparameter Optimization through Neural Network Partitioning
Astroformer: More Data might not be all you need for Classification
Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences
Enhanced Diffusion Sampling via Extrapolation with Multiple ODE Solutions
LUM-ViT: Learnable Under-sampling Mask Vision Transformer for Bandwidth Limited Optical Signal Acquisition
G-PECNet: Towards a Generalizable Pedestrian Trajectory Prediction System
Multi-objective optimization via equivariant deep hypervolume approximation
Enhancing Instance-Level Image Classification with Set-Level Labels
CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modules
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products
Neural Variational Dropout Processes
Beyond FVD: An Enhanced Evaluation Metrics for Video Generation Distribution Quality
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second
STaSy: Score-based Tabular data Synthesis
Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model
EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression
On the Stability of Iterative Retraining of Generative Models on their own Data
A Theory of Dynamic Benchmarks
Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency
Scaling and evaluating sparse autoencoders
Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement
Adapting to Continuously Shifting Domains
Active Learning for Convolutional Neural Networks: A Core-Set Approach
BiPointNet: Binary Neural Network for Point Clouds
A Simple Romance Between Multi-Exit Vision Transformer and Token Reduction
BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments
Can Decoupling Embedded Text from Images Improve Multimodal Learning?
Do GANs learn the distribution? Some Theory and Empirics
Fast Sampling of Diffusion Models with Exponential Integrator
OmniControl: Control Any Joint at Any Time for Human Motion Generation
The Devil is in the Wrongly-classified Samples: Towards Unified Open-set Recognition
An Information Fusion Approach to Learning with Instance-Dependent Label Noise
ARLON: Boosting Diffusion Transformers with Autoregressive Models for Long Video Generation
Environment Predictive Coding for Visual Navigation
Byzantine-Resilient Non-Convex Stochastic Gradient Descent
Human-machine cooperation for semantic feature listing
IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models
Unsupervised Order Learning
Target-Embedding Autoencoders for Supervised Representation Learning
Trajeglish: Traffic Modeling as Next-Token Prediction
Training Unbiased Diffusion Models From Biased Dataset
Steering Protein Family Design through Profile Bayesian Flow
Git Re-Basin: Merging Models modulo Permutation Symmetries
Dynamic Coattention Networks For Question Answering
InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes
Ferret: Refer and Ground Anything Anywhere at Any Granularity
Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability
Grounding Language Plans in Demonstrations Through Counterfactual Perturbations
Critical Points in Quantum Generative Models
Certified Robustness Under Bounded Levenshtein Distance
Counterfactuals uncover the modular structure of deep generative models
GEVRM: Goal-Expressive Video Generation Model For Robust Visual Manipulation
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
cosFormer: Rethinking Softmax In Attention
Multimodal Lego: Model Merging and Fine-Tuning Across Topologies and Modalities in Biomedicine
Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems
ParamΔ for Direct Mixing: Post-Train Large Language Model At Zero Cost
Equivariant Energy-Guided SDE for Inverse Molecular Design
Label-free Concept Bottleneck Models
A Universal Representation Transformer Layer for Few-Shot Image Classification
Encoding word order in complex embeddings
BadEdit: Backdooring Large Language Models by Model Editing
The hidden uniform cluster prior in self-supervised learning
Youku Dense Caption: A Large-scale Chinese Video Dense Caption Dataset and Benchmarks
Towards Federated RLHF with Aggregated Client Preference for LLMs
Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes
Adversarial Policy Gradient for Alternating Markov Games
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks
Accelerating Task Generalisation with Multi-Level Skill Hierarchies
Reproducibility in Machine Learning for Health
The Superposition of Diffusion Models Using the Itô Density Estimator
A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels
Density estimation with LLMs: a geometric investigation of in-context learning trajectories
Diffusion Posterior Sampling for General Noisy Inverse Problems
Large Language Models as Optimizers
Understanding Architectures Learnt by Cell-based Neural Architecture Search
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks
Solving Token Gradient Conflict in Mixture-of-Experts for Large Vision-Language Model
Towards Neural Scaling Laws for Time Series Foundation Models
From Graphs to Hypergraphs: Hypergraph Projection and its Reconstruction
Order Matters: Agent-by-agent Policy Optimization
Topological data analysis on noisy quantum computers
Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks
Efficient Active Imitation Learning with Random Network Distillation
NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition
Unsupervised Pretraining for Fact Verification by Language Model Distillation
Top-N: Equivariant Set and Graph Generation without Exchangeability
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models
Federated Text-driven Prompt Generation for Vision-Language Models
Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models
Reassessing How to Compare and Improve the Calibration of Machine Learning Models
Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
Calibrating Transformers via Sparse Gaussian Processes
MEDFAIR: Benchmarking Fairness for Medical Imaging
Interpreting Knowledge Graph Relation Representation from Word Embeddings
IgGM: A Generative Model for Functional Antibody and Nanobody Design