Most Cited ICLR "embodied interactions" Papers
6,124 papers found • Page 19 of 31
Conference
Selective induction Heads: How Transformers Select Causal Structures in Context
Francesco D'Angelo, francesco croce, Nicolas Flammarion
Student-Informed Teacher Training
Nico Messikommer, Jiaxu Xing, Elie Aljalbout et al.
Learning-Augmented Search Data Structures
Chunkai Fu, Brandon G. Nguyen, Jung Seo et al.
Is Large-scale Pretraining the Secret to Good Domain Generalization?
Piotr Teterwak, Kuniaki Saito, Theodoros Tsiligkaridis et al.
An Information Criterion for Controlled Disentanglement of Multimodal Data
Chenyu Wang, Sharut Gupta, Xinyi Zhang et al.
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
Enshu Liu, Junyi Zhu, Zinan Lin et al.
Counterfactual Concept Bottleneck Models
Gabriele Dominici, Pietro Barbiero, Francesco Giannini et al.
Unveiling the Magic of Code Reasoning through Hypothesis Decomposition and Amendment
Yuze Zhao, Tianyun Ji, Wenjun Feng et al.
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning
Arthur Jacot, Seok Hoan Choi, Yuxiao Wen
Robust Weight Initialization for Tanh Neural Networks with Fixed Point Analysis
Hyunwoo Lee, Hayoung Choi, Hyunju Kim
VAE-Var: Variational Autoencoder-Enhanced Variational Methods for Data Assimilation in Meteorology
Yi Xiao, Qilong Jia, Kun Chen et al.
Stiefel Flow Matching for Moment-Constrained Structure Elucidation
Austin H Cheng, Alston Lo, Kin Long Kelvin Lee et al.
Provable Uncertainty Decomposition via Higher-Order Calibration
Gustaf Ahdritz, Aravind Gollakota, Parikshit Gopalan et al.
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning
Yuxiang Lu, Shengcao Cao, Yu-Xiong Wang
Tuning-Free Bilevel Optimization: New Algorithms and Convergence Analysis
Yifan Yang, Hao Ban, Minhui Huang et al.
Duoduo CLIP: Efficient 3D Understanding with Multi-View Images
Han-Hung Lee, Yiming Zhang, Angel Chang
Provence: efficient and robust context pruning for retrieval-augmented generation
Nadezhda Chirkova, Thibault Formal, Vassilina Nikoulina et al.
Lawma: The Power of Specialization for Legal Annotation
Ricardo Dominguez-Olmedo, Vedant Nanda, Rediet Abebe et al.
LoRA-X: Bridging Foundation Models with Training-Free Cross-Model Adaptation
Farzad Farhadzadeh, Debasmit Das, Shubhankar Borse et al.
Conformal Language Model Reasoning with Coherent Factuality
Maxon Rubin-Toles, Maya Gambhir, Keshav Ramji et al.
Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother et al.
Efficient and Context-Aware Label Propagation for Zero-/Few-Shot Training-Free Adaptation of Vision-Language Model
Yushu Li, Yongyi Su, Adam Goodge et al.
Comparing noisy neural population dynamics using optimal transport distances
Amin Nejatbakhsh, Victor Geadah, Alex Williams et al.
OSDA Agent: Leveraging Large Language Models for De Novo Design of Organic Structure Directing Agents
Zhaolin Hu, Yixiao Zhou, Zhongan Wang et al.
GRAIN: Exact Graph Reconstruction from Gradients
Maria Drencheva, Ivo Petrov, Maximilian Baader et al.
Nesterov acceleration in benignly non-convex landscapes
Kanan Gupta, Stephan Wojtowytsch
Fundamental Limitations on Subquadratic Alternatives to Transformers
Josh Alman, Hantao Yu
Unearthing Skill-level Insights for Understanding Trade-offs of Foundation Models
Mazda Moayeri, Vidhisha Balachandran, Varun Chandrasekaran et al.
Multi-Task Dense Predictions via Unleashing the Power of Diffusion
Yuqi Yang, Peng-Tao Jiang, Qibin Hou et al.
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding
Taiwo Adebiyi, Bach Do, Ruda Zhang
Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing
Keltin Grimes, Marco Christiani, David Shriver et al.
Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference
Matt Riemer, Gopeshh Raaj Subbaraj, Glen Berseth et al.
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
Yu Chen, Jiatai Huang, Yan Dai et al.
Tight Clusters Make Specialized Experts
Stefan Nielsen, Rachel Teo, Laziz Abdullaev et al.
CAMEx: Curvature-aware Merging of Experts
Dung Viet Nguyen, Minh Nguyen, Luc Nguyen et al.
IDInit: A Universal and Stable Initialization Method for Neural Network Training
Yu Pan, Chaozheng Wang, Zekai Wu et al.
Not All LLM-Generated Data Are Equal: Rethinking Data Weighting in Text Classification
Hsun-Yu Kuo, Yin-Hsiang Liao, Yu-Chieh Chao et al.
Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
Hung Le, Dung Nguyen, Kien Do et al.
Spherical Tree-Sliced Wasserstein Distance
Viet-Hoang Tran, Thanh Chu, Minh-Khoi Nguyen-Nhat et al.
UV-Attack: Physical-World Adversarial Attacks on Person Detection via Dynamic-NeRF-based UV Mapping
Yanjie Li, Kaisheng Liang, Bin Xiao
T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data
Hugo Thimonier, José Lucas De Melo Costa, Fabrice Popineau et al.
Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs
Xin Gao, Jian Pu
AdaFisher: Adaptive Second Order Optimization via Fisher Information
Damien GOMES, Yanlei Zhang, Eugene Belilovsky et al.
Self-Normalized Resets for Plasticity in Continual Learning
Vivek Farias, Adam Jozefiak
6D Object Pose Tracking in Internet Videos for Robotic Manipulation
Georgy Ponimatkin, Martin Cífka, Tomas Soucek et al.
Autocorrelation Matters: Understanding the Role of Initialization Schemes for State Space Models
Fusheng Liu, Qianxiao Li
Revisiting a Design Choice in Gradient Temporal Difference Learning
Xiaochi Qian, Shangtong Zhang
Inspection and Control of Self-Generated-Text Recognition Ability in Llama3-8b-Instruct
Christopher Ackerman, Nina Panickssery
Mitigating Reward Over-Optimization in RLHF via Behavior-Supported Regularization
Juntao Dai, Taiye Chen, Yaodong Yang et al.
ELICIT: LLM Augmentation Via External In-context Capability
Futing Wang, Jianhao (Elliott) Yan, Yue Zhang et al.
Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees
Shahryar Zehtabi, Dong-Jun Han, Rohit Parasnis et al.
BrainACTIV: Identifying visuo-semantic properties driving cortical selectivity using diffusion-based image manipulation
Diego García Cerdas, Christina Sartzetaki, Magnus Petersen et al.
LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation
Mufei Li, Viraj Shitole, Eli Chien et al.
Precedence-Constrained Winter Value for Effective Graph Data Valuation
Hongliang Chi, Wei Jin, Charu Aggarwal et al.
Gaussian-Det: Learning Closed-Surface Gaussians for 3D Object Detection
Hongru Yan, Yu Zheng, Yueqi Duan
FedTMOS: Efficient One-Shot Federated Learning with Tsetlin Machine
Shannon How, Jagmohan Chauhan, Geoff Merrett et al.
Ask, and it shall be given: On the Turing completeness of prompting
Ruizhong Qiu, Zhe Xu, Wenxuan Bao et al.
Neural Eulerian Scene Flow Fields
Kyle Vedder, Neehar Peri, Ishan Khatri et al.
Polynomial Composition Activations: Unleashing the Dynamics of Large Language Models
Zhijian Zhuo, Ya Wang, Yutao Zeng et al.
Shedding Light on Time Series Classification using Interpretability Gated Networks
Yunshi Wen, Tengfei Ma, Ronny Luss et al.
State Space Models are Provably Comparable to Transformers in Dynamic Token Selection
Naoki Nishikawa, Taiji Suzuki
Let Me Grok for You: Accelerating Grokking via Embedding Transfer from a Weaker Model
Zhiwei Xu, Zhiyu Ni, Yixin Wang et al.
Large Language Models are Interpretable Learners
Ruochen Wang, Si Si, Felix Yu et al.
Breaking Neural Network Scaling Laws with Modularity
Akhilan Boopathy, Sunshine Jiang, William Yue et al.
Frequency-Guided Masking for Enhanced Vision Self-Supervised Learning
Amin Karimi Monsefi, Mengxi Zhou, Nastaran Monsefi et al.
Biologically Plausible Brain Graph Transformer
Ciyuan Peng, Yuelong Huang, Qichao Dong et al.
Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantification
Santiago Cortes-Gomez, Carlos Patiño, Yewon Byun et al.
Bridging Compressed Image Latents and Multimodal Large Language Models
Chia-Hao Kao, Cheng Chien, Yu-Jen Tseng et al.
GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning
Minghao Xu, Yunteng Geng, Yihang Zhang et al.
DRL: Decomposed Representation Learning for Tabular Anomaly Detection
Hangting Ye, He Zhao, Wei Fan et al.
Bridging the Gap between Database Search and \emph{De Novo} Peptide Sequencing with SearchNovo
Jun Xia, Sizhe Liu, Jingbo Zhou et al.
Many-Objective Multi-Solution Transport
Ziyue Li, Tian Li, Virginia Smith et al.
Point Cluster: A Compact Message Unit for Communication-Efficient Collaborative Perception
Zihan Ding, Jiahui Fu, Si Liu et al.
Stealthy Shield Defense: A Conditional Mutual Information-Based Approach against Black-Box Model Inversion Attacks
Tianqu Zhuang, Hongyao Yu, Yixiang Qiu et al.
BadRobot: Jailbreaking Embodied LLM Agents in the Physical World
Hangtao Zhang, Chenyu Zhu, Xianlong Wang et al.
SigDiffusions: Score-Based Diffusion Models for Time Series via Log-Signature Embeddings
Barbora Barancikova, Zhuoyue Huang, Cristopher Salvi
Data Center Cooling System Optimization Using Offline Reinforcement Learning
Xianyuan Zhan, Xiangyu Zhu, Peng Cheng et al.
Beyond Content Relevance: Evaluating Instruction Following in Retrieval Models
Jianqun Zhou, Yuanlei Zheng, Wei Chen et al.
STAR: Stability-Inducing Weight Perturbation for Continual Learning
Masih Eskandar, Tooba Imtiaz, Davin Hill et al.
Teaching LLMs How to Learn with Contextual Fine-Tuning
Younwoo Choi, Muhammad Adil Asif, Ziwen Han et al.
Cyclic Contrastive Knowledge Transfer for Open-Vocabulary Object Detection
Chuhan ZHANG, Chaoyang Zhu, Pingcheng Dong et al.
Severing Spurious Correlations with Data Pruning
Varun Mulchandani, Jung-Eun Kim
End-to-end Learning of Gaussian Mixture Priors for Diffusion Sampler
Denis Blessing, Xiaogang Jia, Gerhard Neumann
On the Optimal Memorization Capacity of Transformers
Tokio Kajitsuka, Issei Sato
Symmetric Basis Convolutions for Learning Lagrangian Fluid Mechanics
Rene Winchenbach, Nils Thuerey
Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform
Shengyi Huang, Jiayi Weng, Rujikorn Charakorn et al.
Feature Collapse
Thomas Laurent, James von Brecht, Xavier Bresson
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing
Blaise Delattre, Alexandre Araujo, Quentin Barthélemy et al.
Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations
Yujee Song, Donghyun LEE, Rui Meng et al.
Self-Supervised Dataset Distillation for Transfer Learning
Dong Bok Lee, Seanie Lee, Joonho Ko et al.
In defense of parameter sharing for model-compression
Aditya Desai, Anshumali Shrivastava
Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty
Changbin Li, Kangshuo Li, Yuzhe Ou et al.
Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow
Hanyu Zhou, Yi Chang, Haoyue Liu et al.
IceFormer: Accelerated Inference with Long-Sequence Transformers on CPUs
Yuzhen Mao, Martin Ester, Ke Li
A differentiable brain simulator bridging brain simulation and brain-inspired computing
Chaoming Wang, Tianqiu Zhang, Sichao He et al.
Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks
Sung Moon Ko, Sumin Lee, Dae-Woong Jeong et al.
Provably Efficient CVaR RL in Low-rank MDPs
Yulai Zhao, Wenhao Zhan, Xiaoyan Hu et al.
Time Fairness in Online Knapsack Problems
Adam Lechowicz, Rik Sengupta, Bo Sun et al.
Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning
Mirco Mutti, Riccardo De Santi, Marcello Restelli et al.
Consistent algorithms for multi-label classification with macro-at-$k$ metrics
Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch et al.
Multi-View Representation is What You Need for Point-Cloud Pre-Training
Siming Yan, Chen Song, Youkang Kong et al.
Entropy Coding of Unordered Data Structures
Julius Kunze, Daniel Severo, giulio zani et al.
Differentiable Learning of Generalized Structured Matrices for Efficient Deep Neural Networks
Changwoo Lee, Hun-Seok Kim
Conditional Variational Diffusion Models
Gabriel della Maggiora, Luis A. Croquevielle, Nikita Deshpande et al.
TRAM: Bridging Trust Regions and Sharpness Aware Minimization
Tom Sherborne, Naomi Saphra, Pradeep Dasigi et al.
The Curse of Diversity in Ensemble-Based Exploration
Zhixuan Lin, Pierluca D'Oro, Evgenii Nikishin et al.
Contextual Bandits with Online Neural Regression
Rohan Deb, Yikun Ban, Shiliang Zuo et al.
REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes
David Ireland, Giovanni Montana
LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks
Jianlang Chen, Xuhong Ren, Qing Guo et al.
Explaining Kernel Clustering via Decision Trees
Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks
Federico Errica, Mathias Niepert
Expressivity of ReLU-Networks under Convex Relaxations
Maximilian Baader, Mark N Müller, Yuhao Mao et al.
Embodied Active Defense: Leveraging Recurrent Feedback to Counter Adversarial Patches
Lingxuan Wu, Xiao Yang, Yinpeng Dong et al.
Generating Pragmatic Examples to Train Neural Program Synthesizers
Saujas Vaduguru, Daniel Fried, Yewen Pu
Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer
Xingyu Liu, Deepak Pathak, DING ZHAO
From Graphs to Hypergraphs: Hypergraph Projection and its Reconstruction
Yanbang Wang, Jon Kleinberg
Koopman-based generalization bound: New aspect for full-rank weights
Yuka Hashimoto, Sho Sonoda, Isao Ishikawa et al.
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models
Ehsan Mokhtarian, Saber Salehkaleybar, AmirEmad Ghassami et al.
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
Jianliang He, Han Zhong, Zhuoran Yang
Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Models
Tianjian Li, Haoran Xu, Philipp Koehn et al.
Adversarial Imitation Learning via Boosting
Jonathan Chang, Dhruv Sreenivas, Yingbing Huang et al.
Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants
Peter Richtarik, Elnur Gasanov, Konstantin Burlachenko
ModuLoRA: Finetuning 2-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers
Junjie Oscar Yin, Yingheng Wang, Volodymyr Kuleshov et al.
Statistically Optimal $K$-means Clustering via Nonnegative Low-rank Semidefinite Programming
Yubo Zhuang, Xiaohui Chen, Yun Yang et al.
Augmenting Transformers with Recursively Composed Multi-grained Representations
Xiang Hu, Qingyang Zhu, Kewei Tu et al.
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates
Nicholas Corrado, Josiah Hanna
A Mutual Information Perspective on Federated Contrastive Learning
Christos Louizos, Matthias Reisser, Denis Korzhenkov
Reconciling Spatial and Temporal Abstractions for Goal Representation
Mehdi Zadem, Sergio Mover, Sao Mai Nguyen
Alice Benchmarks: Connecting Real World Re-Identification with the Synthetic
Xiaoxiao Sun, Yue Yao, Shengjin Wang et al.
Analyzing and Improving Optimal-Transport-based Adversarial Networks
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations
Ruiquan Huang, Yingbin Liang, Jing Yang
Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation
Yuxiang (YU-HSIANG) LAI, Yi Zhou, Xinghong Liu et al.
Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments
Yang Yang, Wenhai Wang, Zhe Chen et al.
Towards Meta-Pruning via Optimal Transport
Alexander Theus, Olin Geimer, Friedrich Wicke et al.
Function-space Parameterization of Neural Networks for Sequential Learning
Aidan Scannell, Riccardo Mereu, Paul Chang et al.
Annealing Self-Distillation Rectification Improves Adversarial Training
Yu-Yu Wu, Hung-Jui Wang, Shang-Tse Chen
Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation
Wenxuan Zhang, Youssef Mohamed, Bernard Ghanem et al.
Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data
Shikai Fang, Xin Yu, Zheng Wang et al.
Win-Win: Training High-Resolution Vision Transformers from Two Windows
Vincent Leroy, Jerome Revaud, Thomas Lucas et al.
Distributionally Robust Optimization with Bias and Variance Reduction
Ronak Mehta, Vincent Roulet, Krishna Pillutla et al.
Fast Hyperboloid Decision Tree Algorithms
Philippe Chlenski, Ethan Turok, Antonio Moretti et al.
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing
Vincent Grari, Thibault Laugel, Tatsunori Hashimoto et al.
Learning to Solve Bilevel Programs with Binary Tender
Bo Zhou, Ruiwei Jiang, Siqian Shen
Reinforcement Symbolic Regression Machine
Yilong Xu, Yang Liu, Hao Sun
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
Haozhe Jiang, Qiwen Cui, Zhihan Xiong et al.
Repelling Random Walks
Isaac Reid, Eli Berger, Krzysztof Choromanski et al.
PlaSma: Procedural Knowledge Models for Language-based Planning and Re-Planning
Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin et al.
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
Jiacheng Guo, Minshuo Chen, Huan Wang et al.
Quantifying the Plausibility of Context Reliance in Neural Machine Translation
Gabriele Sarti, Grzegorz Chrupała, Malvina Nissim et al.
Fast and unified path gradient estimators for normalizing flows
Lorenz Vaitl, Ludwig Winkler, Lorenz Richter et al.
Out-of-Variable Generalisation for Discriminative Models
Siyuan Guo, Jonas Wildberger, Bernhard Schoelkopf
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios
Reward Learning from Multiple Feedback Types
Yannick Metz, Andras Geiszl, Raphaël Baur et al.
MetaDesigner: Advancing Artistic Typography through AI-Driven, User-Centric, and Multilingual WordArt Synthesis
Jun-Yan He, Zhi-Qi Cheng, Chenyang Li et al.
Strategic Classification With Externalities
Safwan Hossain, Evi Micha, Yiling Chen et al.
Risk Bounds of Accelerated SGD for Overparameterized Linear Regression
Xuheng Li, Yihe Deng, Jingfeng Wu et al.
Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling
Aram Davtyan, Leello Dadi, Volkan Cevher et al.
Learning Graph Invariance by Harnessing Spuriosity
Tianjun Yao, Yongqiang Chen, Kai Hu et al.
TODO: Enhancing LLM Alignment with Ternary Preferences
Yuxiang Guo, Lu Yin, Bo Jiang et al.
High-Precision Dichotomous Image Segmentation via Probing Diffusion Capacity
Qian Yu, Peng-Tao Jiang, Hao Zhang et al.
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training
Shruthi Gowda, Bahram Zonooz, Elahe Arani
Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation
Wenxuan Bao, Zhichen Zeng, Zhining Liu et al.
Projection Head is Secretly an Information Bottleneck
Zhuo Ouyang, Kaiwen Hu, Qi Zhang et al.
Where Am I and What Will I See: An Auto-Regressive Model for Spatial Localization and View Prediction
Junyi Chen, Di Huang, Weicai Ye et al.
Anti-Exposure Bias in Diffusion Models
Junyu Zhang, Daochang Liu, Eunbyung Park et al.
Doubly Optimal Policy Evaluation for Reinforcement Learning
Shuze Liu, Claire Chen, Shangtong Zhang
Accelerating Training with Neuron Interaction and Nowcasting Networks
Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie et al.
GSE: Group-wise Sparse and Explainable Adversarial Attacks
Shpresim Sadiku, Moritz Wagner, Sebastian Pokutta
eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels
Alexander DeRieux, Walid Saad
CL-DiffPhyCon: Closed-loop Diffusion Control of Complex Physical Systems
Long Wei, Haodong Feng, Yuchen Yang et al.
Metamizer: A Versatile Neural Optimizer for Fast and Accurate Physics Simulations
Nils Wandel, Stefan Schulz, Reinhard Klein
SysBench: Can LLMs Follow System Message?
Yanzhao Qin, Tao Zhang, Tao Zhang et al.
SAM-CP: Marrying SAM with Composable Prompts for Versatile Segmentation
Pengfei Chen, Lingxi Xie, xinyue huo et al.
Contextualizing biological perturbation experiments through language
Menghua (Rachel) Wu, Russell Littman, Jacob Levine et al.
QMP: Q-switch Mixture of Policies for Multi-Task Behavior Sharing
Grace Zhang, Ayush Jain, Injune Hwang et al.
Adaptive Retention & Correction: Test-Time Training for Continual Learning
Haoran Chen, Micah Goldblum, Zuxuan Wu et al.
Graph Assisted Offline-Online Deep Reinforcement Learning for Dynamic Workflow Scheduling
Yifan Yang, Gang Chen, Hui Ma et al.
StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning
Shengzhong Zhang, Wenjie Yang, Xinyuan Cao et al.
Towards Homogeneous Lexical Tone Decoding from Heterogeneous Intracranial Recordings
Di Wu, Siyuan Li, Chen Feng et al.
The Effective Horizon Explains Deep RL Performance in Stochastic Environments
Cassidy Laidlaw, Banghua Zhu, Stuart Russell et al.
Offline Hierarchical Reinforcement Learning via Inverse Optimization
Carolin Schmidt, Daniele Gammelli, James Harrison et al.
Manifold Induced Biases for Zero-shot and Few-shot Detection of Generated Images
Jonathan Brokman, Amit Giloni, Omer Hofman et al.
Towards Generative Abstract Reasoning: Completing Raven’s Progressive Matrix via Rule Abstraction and Selection
Fan Shi, Bin Li, Xiangyang Xue
Efficient Multi-agent Offline Coordination via Diffusion-based Trajectory Stitching
Lei Yuan, Yuqi Bian, Lihe Li et al.
MaRS: A Fast Sampler for Mean Reverting Diffusion based on ODE and SDE Solvers
Ao Li, Wei Fang, Hongbo Zhao et al.
Multi-Scale Fusion for Object Representation
Rongzhen Zhao, Vivienne Huiling Wang, Juho Kannala et al.
An Evolved Universal Transformer Memory
Edoardo Cetin, Qi Sun, Tianyu Zhao et al.
3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery
Xiuyuan Hu, Guoqing Liu, Can Chen et al.
Black Sheep in the Herd: Playing with Spuriously Correlated Attributes for Vision-Language Recognition
Xinyu Tian, Shu Zou, Zhaoyuan Yang et al.
Incorporating Visual Correspondence into Diffusion Model for Virtual Try-On
Siqi Wan, Jingwen Chen, Yingwei Pan et al.
Exploring the Design Space of Visual Context Representation in Video MLLMs
Yifan Du, Yuqi Huo, Kun Zhou et al.
A Policy Gradient Method for Confounded POMDPs
Mao Hong, Zhengling Qi, Yanxun Xu
Enhancing Neural Training via a Correlated Dynamics Model
Jonathan Brokman, Roy Betser, Rotem Turjeman et al.
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model
Liyang Zhu, Meng Ding, Vaneet Aggarwal et al.
Exploring a Principled Framework for Deep Subspace Clustering
Xianghan Meng, Zhiyuan Huang, Wei He et al.
Diversity-Rewarded CFG Distillation
Geoffrey Cideron, Andrea Agostinelli, Johan Ferret et al.
A Characterization Theorem for Equivariant Networks with Point-wise Activations
Marco Pacini, Xiaowen Dong, Bruno Lepri et al.
UTILITY: Utilizing Explainable Reinforcement Learning to Improve Reinforcement Learning
Shicheng Liu, Minghui Zhu
Analytic DAG Constraints for Differentiable DAG Learning
Zhen Zhang, Ignavier Ng, Dong Gong et al.
Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis
Weiwei Lin, Chenhang HE