Table of Contents

• EMO: Episodic Memory Optimization for Few-Shot Meta-LearningYingjun Du, Jiayi Shen, Xiantong Zhen, Cees G. M. Snoek. 1-20 [doi]
• Replay Buffer with Local Forgetting for Adapting to Local Environment Changes in Deep Model-Based Reinforcement LearningAli Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Harm van Seijen, Sarath Chandar. 21-42 [doi]
• Challenging Common Assumptions about Catastrophic Forgetting and Knowledge AccumulationTimothée Lesort, Oleksiy Ostapenko, Pau Rodríguez, Diganta Misra, Md Rifat Arefin, Laurent Charlin, Irina Rish. 43-65 [doi]
• Differentially Private Algorithms for Efficient Online Matroid OptimizationKushagra Chandak, Bingshan Hu, Nidhi Hegde 0001. 66-88 [doi]
• Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming ChallengesMassimo Caccia, Jonas Mueller 0001, Taesup Kim, Laurent Charlin, Rasool Fakoor. 89-119 [doi]
• Vision-Language Models as Success DetectorsYuqing Du, Ksenia Konyushkova, Misha Denil, Akhil Raju, Jessica Landon, Felix Hill, Nando de Freitas, Serkan Cabi. 120-136 [doi]
• Autotelic Reinforcement Learning in Multi-Agent EnvironmentsEleni Nisioti, Elías Masquil, Gautier Hamon, Clément Moulin-Frier. 137-161 [doi]
• Fine-grain Inference on Out-of-Distribution Data with Hierarchical ClassificationRandolph Linderman, Jingyang Zhang, Nathan Inkawhich, Hai Helen Li, Yiran Chen. 162-183 [doi]
• The Effectiveness of World Models for Continual Reinforcement LearningSamuel Kessler, Mateusz Ostaszewski, Michal Pawel Bortkiewicz, Mateusz Zarski, Maciej Wolczyk, Jack Parker-Holder, Stephen J. Roberts, Piotr Milos. 184-204 [doi]
• Augmenting Autotelic Agents with Large Language ModelsCédric Colas, Laetitia Teodorescu, Pierre-Yves Oudeyer, Xingdi Yuan, Marc-Alexandre Côté. 205-226 [doi]
• Towards Single Source Domain Generalisation in Trajectory Prediction: A Motion Prior based ApproachRenhao Huang, Anthony Tompkins, Maurice Pagnucco, Yang Song 0001. 227-243 [doi]
• RaSP: Relation-aware Semantic Prior for Weakly Supervised Incremental SegmentationSubhankar Roy, Riccardo Volpi, Gabriela Csurka, Diane Larlus. 244-269 [doi]
• Stabilizing Unsupervised Environment Design with a Learned AdversaryIshita Mediratta, Minqi Jiang, Jack Parker-Holder, Michael Dennis 0001, Eugene Vinitsky, Tim Rocktäschel. 270-291 [doi]
• Learning Meta Representations for Agents in Multi-Agent Reinforcement LearningShenao Zhang, Li Shen 0005, Lei Han, Li Shen 0008. 292-317 [doi]
• Partial Hypernetworks for Continual LearningHamed Hemati, Vincenzo Lomonaco, Davide Bacciu, Damian Borth. 318-336 [doi]
• Human inductive biases for aversive continual learning - a hierarchical Bayesian nonparametric modelSashank Pisupati, Isabel M. Berwian, Jamie Chiu, Yongjing Ren, Yael Niv. 337-346 [doi]
• Prospective Learning: Principled Extrapolation to the FutureAshwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang 0004, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein. 347-357 [doi]
• Embodied Active Learning of Relational State Abstractions for Bilevel PlanningAmber Li, Tom Silver. 358-375 [doi]
• Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale LearningHadi Nekoei, Akilesh Badrinaaraayanan, Amit Sinha, Mohammad Amini, Janarthanan Rajendran, Aditya Mahajan, Sarath Chandar. 376-398 [doi]
• PlaStIL: Plastic and Stable Exemplar-Free Class-Incremental LearningGrégoire Petit, Adrian Popescu 0001, Eden Belouadah, David Picard, Bertrand Delezoide. 399-414 [doi]
• Partial Index Tracking: A Meta-Learning ApproachYongxin Yang, Timothy M. Hospedales. 415-436 [doi]
• Class-Incremental Learning with RepetitionHamed Hemati, Andrea Cossu, Antonio Carta, Julio Hurtado, Lorenzo Pellegrini, Davide Bacciu, Vincenzo Lomonaco, Damian Borth. 437-455 [doi]
• Reducing Communication Overhead in Federated Learning for Pre-trained Language Models Using Parameter-Efficient FinetuningShubham Malaviya, Manish Shukla 0001, Sachin Lodha. 456-469 [doi]
• Time and temporal abstraction in continual learning: tradeoffs, analogies and regret in an active measuring settingVincent Létourneau, Colin Bellinger, Isaac Tamblyn, Maia Fraser. 470-480 [doi]
• Self-trained Centroid Classifiers for Semi-supervised Cross-domain Few-shot LearningHongyu Wang 0008, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes 0001. 481-492 [doi]
• Evaluating Continual Learning on a Home RobotSam Powers, Abhinav Gupta 0001, Chris Paxton. 493-512 [doi]
• Fixed Design Analysis of Regularization-Based Continual LearningHaoran Li 0006, Jingfeng Wu, Vladimir Braverman. 513-533 [doi]
• Continually learning representations at scaleAlexandre Galashov, Jovana Mitrovic, Dhruva Tirumala, Yee Whye Teh, Timothy Nguyen, Arslan Chaudhry, Razvan Pascanu. 534-547 [doi]
• Minimal Value-Equivalent Partial Models for Scalable and Robust Planning in Lifelong Reinforcement LearningSafa Alver, Doina Precup. 548-567 [doi]
• Hierarchical Representation Learning for Markov Decision ProcessesLorenzo Steccanella, Simone Totaro, Anders Jonsson 0001. 568-585 [doi]
• MultiMix TFT: A Multi-task Mixed-Frequency Framework with Temporal Fusion TransformersBoje Deforce, Bart Baesens, Jan Diels, Estefanía Serral Asensio. 586-600 [doi]
• What Happens During Finetuning of Vision Transformers: An Invariance Based InvestigationGabriele Merlin, Vedant Nanda, Ruchit Rawal, Mariya Toneva. 601-619 [doi]
• Loss of Plasticity in Continual Deep Reinforcement LearningZaheer Abbas, Rosie Zhao, Joseph Modayil, Adam White 0001, Marlos C. Machado. 620-636 [doi]
• Sample-Efficient Learning of Novel Visual ConceptsSarthak Bhagat, Simon Stepputtis, Joseph Campbell, Katia P. Sycara. 637-657 [doi]
• VIBR: Learning View-Invariant Value Functions for Robust Visual ControlTom Dupuis, Jaonary Rabarisoa, Quoc-Cuong Pham, David Filliat. 658-682 [doi]
• Incremental Unsupervised Domain Adaptation on Evolving GraphsHsing-Huan Chung, Joydeep Ghosh. 683-702 [doi]
• Auxiliary task discovery through generate-and-testBanafsheh Rafiee, Sina Ghiassian, Jun Jin 0001, Richard S. Sutton, Jun Luo 0009, Adam White 0001. 703-714 [doi]
• Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision ProcessesRéda Alami, Mohammed Mahfoud, Eric Moulines. 715-744 [doi]
• Value-aware Importance Weighting for Off-policy Reinforcement LearningKristopher De Asis, Eric Graves 0002, Richard S. Sutton. 745-763 [doi]
• Re-Weighted Softmax Cross-Entropy to Control Forgetting in Federated LearningGwen Legate, Lucas Caccia, Eugene Belilovsky. 764-780 [doi]
• Measuring and Mitigating Interference in Reinforcement LearningVincent Liu, Han Wang, Ruo Yu Tao, Khurram Javed, Adam White 0001, Martha White. 781-795 [doi]
• Adaptive Meta-Learning via data-dependent PAC-Bayes boundsLior Friedman, Ron Meir. 796-810 [doi]
• Active Class Selection for Few-Shot Class-Incremental LearningChristopher McClurg, Ali Ayub, Harsh Tyagi, Sarah Michele Rajtmajer, Alan R. Wagner. 811-827 [doi]
• Improving Online Continual Learning Performance and Stability with Temporal EnsemblesAlbin Soutif-Cormerais, Antonio Carta, Joost van de Weijer 0001. 828-845 [doi]
• Model-Based Meta Automatic Curriculum LearningZifan Xu, Yulin Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian Jiang, Bo Liu, Peter Stone. 846-860 [doi]
• Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of HanabiHadi Nekoei, Xutong Zhao, Janarthanan Rajendran, Miao Liu, Sarath Chandar. 861-877 [doi]
• Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy ImitationMassimiliano Patacchiola, Mingfei Sun, Katja Hofmann, Richard E. Turner. 878-908 [doi]
• Substituting Data Annotation with Balanced Neighbourhoods and Collective Loss in Multi-label Text ClassificationMuberra Ozmen, Joseph Cotnareanu, Mark Coates. 909-922 [doi]
• I2I: Initializing Adapters with Improvised KnowledgeTejas Srinivasan, Furong Jia, Mohammad Rostami, Jesse Thomason. 923-935 [doi]
• Sharing Lifelong Reinforcement Learning Knowledge via Modulating MasksSaptarshi Nath, Christos Peridis, Eseoghene Ben-Iwhiwhu, Xinran Liu, Shirin Dora, Cong Liu, Soheil Kolouri, Andrea Soltoggio. 936-960 [doi]
• Continual Learning Beyond a Single ModelThang Doan, Seyed-Iman Mirzadeh, Mehrdad Farajtabar. 961-991 [doi]
• Improving Performance in Continual Learning Tasks using Bio-Inspired ArchitecturesSandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash. 992-1008 [doi]
• A Minimalist Approach for Domain Adaptation with Optimal TransportArip Asadulaev, Vitaly Shutov, Alexander Korotin, Alexander Panfilov, Vladislava Kontsevaya, Andrey Filchenkov. 1009-1024 [doi]
• Low-rank extended Kalman filtering for online learning of neural networks from streaming dataPeter G. Chang, Gerardo Duràn-Martín, Alexander Y. Shestopaloff, Matt Jones 0002, Kevin Patrick Murphy. 1025-1071 [doi]
• Introspective Action Advising for Interpretable Transfer LearningJoseph Campbell, Yue Guo, Fiona Xie, Simon Stepputtis, Katia P. Sycara. 1072-1090 [doi]
• SF-FSDA: Source-Free Few-Shot Domain Adaptive Object Detection with Efficient Labeled Data FactoryHan Sun, Rui Gong, Konrad Schindler, Luc Van Gool. 1091-1111 [doi]