NeurIP2023-Continual-Learning-Papers

[1] Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors

• 🧑‍🔬 Authors: Thomas Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi
• 🏫 Affiliations: University of Virginia, MIT, Sony AI,  Microsoft Research
• 🔗 Links: [arXiv:2211.11031] [OpenReview] [Code]

[2] An Empirical Investigation of the Role of Pre-training in Lifelong Learning

• 🧑‍🔬 Authors: Sanket Vaibhav Mehta, Darshan Patil, Sarath Chandar, Emma Strubell
• 🏫 Affiliations: Carnegie Mellon University, Université de Montréal, Mila - Quebec AI Institute
• 🔗 Links: [arXiv:2112.09153] [JMLR] [Code]

[3] LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning

• 🧑‍🔬 Authors: Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, Peter Stone
• 🏫 Affiliations: The University of Texas at Austin, Sony AI, Tsinghua University
• 🔗 Links: [arXiv:2306.03310] [OpenReview] [Code]

[4] Temporal Continual Learning with Prior Compensation for Human Motion Prediction

• 🧑‍🔬 Authors: Jianwei Tang, Jiangxin Sun, Xiaotong Lin, Lifang Zhang, Wei-Shi Zheng, Jian-Fang Hu
• 🏫 Affiliations: Sun Yat-sen University, Dongguan University of Technology
• 🔗 Links: [OpenReview] [Code]

[5] Prediction and Control in Continual Reinforcement Learning

• 🧑‍🔬 Authors: Nishanth Anand, Doina Precup
• 🏫 Affiliations: McGill University, Mila, and Deepmind
• 🔗 Links: [OpenReview]

[6] Continual Distinct Elements in the Turnstile Model with Differential Privacy under Continual Observation

• 🧑‍🔬 Authors: Palak Jain, Iden Kalemaj, Sofya Raskhodnikova, Satchit Sivakumar, Adam Smith
• 🏫 Affiliations: Boston University
• 🔗 Links: [arXiv:2306.06723] [OpenReview]

[7] A Definition of Continual Reinforcement Learning

• 🧑‍🔬 Authors: David Abel, André Barreto, Benjamin Van Roy, Doina Precup, Hado van Hasselt, Satinder Singh
• 🏫 Affiliations: Google DeepMind
• 🔗 Links: [arXiv:2307.11046] [OpenReview]

[8] TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and Promotion

• 🧑‍🔬 Authors: Preetha Vijayan, Prashant Bhat, Elahe Arani, Bahram Zonooz
• 🏫 Affiliations: NavInfo Europe, Eindhoven University of Technology, TomTom
• 🔗 Links: [arXiv:2310.08217] [OpenReview] [Code]

[9] Recasting Continual Learning as Sequence Modeling

• 🧑‍🔬 Authors: Soochan Lee, Jaehyeon Son, Gunhee Kim
• 🏫 Affiliations: Seoul National University
• 🔗 Links: [arXiv:] [OpenReview] [Code]

[10] Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation

• 🧑‍🔬 Authors: Yilin Lyu, Liyuan Wang, Xingxing Zhang, Zicheng Sun, Hang Su, Jun Zhu, Liping Jing
• 🏫 Affiliations: Beijing Jiaotong University, THBI Lab, Tsinghua University
• 🔗 Links: [arXiv:] [OpenReview] [Code]

[11] COOM: A Game Benchmark for Continual Reinforcement Learning

• 🧑‍🔬 Authors: Tristan Tomilin, Meng Fang, Yudi Zhang, Mykola Pechenizkiy
• 🏫 Affiliations: Eindhoven University of Technology, University of Liverpool
• 🔗 Links: [OpenReview] [Code]

[12] Continual Learning for Instruction Following from Realtime Feedback

• 🧑‍🔬 Authors: Alane Suhr, Yoav Artzi
• 🏫 Affiliations: University of California, Berkeley, Cornell University
• 🔗 Links: [arXiv:] [OpenReview]

[13] A Smooth Binary Mechanism for Efficient Private Continual Observation

• 🧑‍🔬 Authors: Joel Daniel Andersson, Rasmus Pagh
• 🏫 Affiliations: University of Copenhagen
• 🔗 Links: [arXiv:] [OpenReview]

[14] CLeAR: Continual Learning on Algorithmic Reasoning for Human-like Intelligence

• 🧑‍🔬 Authors: Bong Gyun Kang, HyunGi Kim, Dahuin Jung, Sungroh Yoon
• 🏫 Affiliations: Seoul National University
• 🔗 Links: [OpenReview] [Code]

[15] Parameterizing Context: Unleashing the Power of Parameter-Efficient Fine-Tuning and In-Context Tuning for Continual Table Semantic Parsing

• 🧑‍🔬 Authors: Yongrui Chen, Shenyu Zhang, Guilin Qi, Xinnan Guo
• 🏫 Affiliations: Southeast University
• 🔗 Links: [arXiv:] [OpenReview]

[16] RDumb: A simple approach that questions our progress in continual test-time adaption

• 🧑‍🔬 Authors: Ori Press, Steffen Schneider, Matthias Kuemmerer, Matthias Bethge
• 🏫 Affiliations: 1University of Tubingen, EPFL
• 🔗 Links: [arXiv:] [OpenReview] [Code]

[17] Augmented Memory Replay-based Continual Learning Approaches for Network Instruction Detection

• 🧑‍🔬 Authors: Suresh kumar Amalapuram, Sumohana S. Channappayya, Bheemarjuna Tamma
• 🏫 Affiliations: Indian Institute of Technology Hyderabad
• 🔗 Links: [OpenReview]

[18] Loss Decoupling for Task-Agnostic Continual Learning

• 🧑‍🔬 Authors: Yan-Shuo Liang, Wu-Jun Li
• 🏫 Affiliations: Nanjing University
• 🔗 Links: [OpenReview]

[19] On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm

• 🧑‍🔬 Authors: Qi CHEN, Changjian Shui, Ligong Han, Mario Marchand
• 🏫 Affiliations: Laval University, McGill University, Rutgers University
• 🔗 Links: [OpenReview]

[20] FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning

• 🧑‍🔬 Authors: Dipam Goswami, Yuyang Liu, Bartłomiej Twardowski, Joost van de Weijer
• 🏫 Affiliations: Universitat Autònoma de Barcelona, Computer Vision Center, Barcelona, University of Chinese Academy of Sciences, Chinese Academy of Sciences, IDEAS-NCBR
• 🔗 Links: [arXiv:] [OpenReview] [Code]

[21] Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments

• 🧑‍🔬 Authors: Thanh-Dat Truong, Hoang-Quan Nguyen, Bhiksha Raj, Khoa Luu
• 🏫 Affiliations: University of Arkansas, Carnegie Mellon University, Mohammed bin Zayed University of AI
• 🔗 Links: [arXiv:] [OpenReview]

[22] Hierachical Decomposition of Prompt-Based Continual Learning: Rethinging Obscured Sub-optimality

• 🧑‍🔬 Authors: Liyuan Wang, Jingyi Xie, Xingxing Zhang, Mingyi Huang, Hang Su, Jun Zhu
• 🏫 Affiliations: Tsinghua University
• 🔗 Links: [arXiv:] [OpenReview] [Code]

[23] An Efficient Dataset Condensation Plugin and Its Application to Continual Learning

• 🧑‍🔬 Authors: Enneng Yang, Li Shen, Zhenyi Wang, Tongliang Liu, Guibing Guo
• 🏫 Affiliations: Northeastern University, China, JD Explore Academy, University of Maryland, The University of Sydney
• 🔗 Links: [OpenReview]

[24] Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm

• 🧑‍🔬 Authors:
• 🏫 Affiliations: George Mason University, University at Buffalo
• 🔗 Links: [OpenReview] [Code]

[25] CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation

• 🧑‍🔬 Authors: Xiuzhe Wu, Peng Dai, Weipeng DENG, Handi Chen, Yang Wu, Yan-Pei Cao, Ying Shan, XIAOJUAN QI
• 🏫 Affiliations: The University of Hong Kong, Tencent AI Lab, ARC Lab, Tencent PCG
• 🔗 Links: [OpenReview] [Code]

[26] Evolving Standardization for Continual Domain Generalization over Temporal Drift

• 🧑‍🔬 Authors: Mixue Xie, Shuang Li, Longhui Yuan, Chi Harold Liu, Zehui Dai
• 🏫 Affiliations: Beijing Institute of Technology, Lazada Search & Monetisation Tech
• 🔗 Links: [OpenReview]

[27] RanPAC: Random Projections and Pretrained Models for Continual Learning

• 🧑‍🔬 Authors: Mark D. McDonnell, Dong Gong, Amin Parveneh, Ehsan Abbasnejad, Anton van den Hengel
• 🏫 Affiliations: The University of Adelaide, University of New South Wales
• 🔗 Links: [arXiv:] [OpenReview] [Code]

[28] Selective Amnesia: A Continual Learning Approach for Forgetting in Deep Generative Models

• 🧑‍🔬 Authors: Alvin Heng, Harold Soh
• 🏫 Affiliations: National University of Singapore
• 🔗 Links: [arXiv:] [OpenReview] [Code]

[29] Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework

• 🧑‍🔬 Authors: Weiduo Liao, Ying Wei, Mingchen Jiang, Qingfu Zhang, Hisao Ishibuchi
• 🏫 Affiliations: City University of Hong Kong, Southern University of Science and Technology
• 🔗 Links: [OpenReview] [Code]

[30] NPCL: Neural Processes for Uncertainty-Aware Continual Learning

• 🧑‍🔬 Authors: Saurav Jha, Dong Gong, He Zhao, Lina Yao
• 🏫 Affiliations: UNSW, CSIRO’s Data61
• 🔗 Links: [arXiv:] [OpenReview] [Code]

[31] A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks

• 🧑‍🔬 Authors: Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr
• 🏫 Affiliations: University of Southern California, FedML
• 🔗 Links: [arXiv:] [OpenReview]

[32] Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration

• 🧑‍🔬 Authors: Qi-Wei Wang, Da-Wei Zhou, Yi-Kai Zhang, De-Chuan Zhan, Han-Jia Ye
• 🏫 Affiliations: Nanjing University
• 🔗 Links: [arXiv:] [OpenReview] [Code]

[33] A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm

• 🧑‍🔬 Authors: Haizhou Shi, Hao Wang
• 🏫 Affiliations: Rutgers University
• 🔗 Links: [arXiv:] [OpenReview] [Code]

[34] Saving 100x Storage: Prototype Replay for Reconstructing Training Sample Distribution in Class-Incremental Semantic Segmentation

• 🧑‍🔬 Authors: Jinpeng Chen, Runmin Cong, Yuxuan LUO, Horace Ip, Sam Kwong
• 🏫 Affiliations: City University of Hong Kong, Shandong University, Lingnan University
• 🔗 Links: [OpenReview] [Code]

[35] Enhancing Knowledge Transfer for Task Incremental Learning with Data-Free Subnetwork

• 🧑‍🔬 Authors: Qiang Gao, Xiaojun Shan, Yuchen Zhang, Fan Zhou
• 🏫 Affiliations: Southwestern University of Finance and Economics, University of Electronic Science and Technology of China
• 🔗 Links: [OpenReview]