{"total":1010,"rows":[{"id":"2302.00487","title":"A Comprehensive Survey of Continual Learning: Theory, Method and Application","created":"2023-01-31","cited_by_count":872,"area":null},{"id":"2103.12352","title":"iMAP: Implicit Mapping and Positioning in Real-Time","created":"2021-03-23","cited_by_count":476,"area":null},{"id":"2211.13218","title":"CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning","created":"2022-11-23","cited_by_count":450,"area":null},{"id":"2303.15361","title":"A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts","created":"2023-03-27","cited_by_count":359,"area":null},{"id":"2103.09762","title":"Gradient Projection Memory for Continual Learning","created":"2021-03-17","cited_by_count":348,"area":null},{"id":"2111.11326","title":"DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion","created":"2021-11-22","cited_by_count":291,"area":null},{"id":"2103.17230","title":"Rainbow Memory: Continual Learning with a Memory of Diverse Samples","created":"2021-03-31","cited_by_count":273,"area":null},{"id":"2109.12894","title":"Training Spiking Neural Networks Using Lessons From Deep Learning","created":"2021-09-27","cited_by_count":259,"area":null},{"id":"2207.12819","title":"S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning","created":"2022-07-26","cited_by_count":246,"area":null},{"id":"2101.10423","title":"Online Continual Learning in Image Classification: An Empirical Survey","created":"2021-01-25","cited_by_count":245,"area":null},{"id":"2302.03648","title":"Class-Incremental Learning: A Survey","created":"2023-02-07","cited_by_count":209,"area":null},{"id":"2302.03241","title":"Continual Pre-training of Language Models","created":"2023-02-07","cited_by_count":198,"area":null},{"id":"2208.05592","title":"Patching open-vocabulary models by interpolating weights","created":"2022-08-10","cited_by_count":190,"area":null},{"id":"2104.03047","title":"Few-Shot Incremental Learning with Continually Evolved Classifiers","created":"2021-04-07","cited_by_count":187,"area":null},{"id":"2303.07338","title":"Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need","created":"2023-03-13","cited_by_count":184,"area":null},{"id":"2305.10120","title":"Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models","created":"2023-05-17","cited_by_count":177,"area":null},{"id":"2205.12393","title":"Fine-tuned Language Models are Continual Learners","created":"2022-05-24","cited_by_count":156,"area":null},{"id":"2205.13218","title":"A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning","created":"2022-05-26","cited_by_count":154,"area":null},{"id":"2112.04215","title":"Self-Supervised Models are Continual Learners","created":"2021-12-08","cited_by_count":149,"area":null},{"id":"2402.01364","title":"Continual Learning for Large Language Models: A Survey","created":"2024-02-02","cited_by_count":147,"area":null},{"id":"2103.07113","title":"Training Networks in Null Space of Feature Covariance for Continual Learning","created":"2021-03-12","cited_by_count":143,"area":null},{"id":"2305.18703","title":"Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey","created":"2023-05-30","cited_by_count":135,"area":null},{"id":"2112.09153","title":"An Empirical Investigation of the Role of Pre-training in Lifelong Learning","created":"2021-12-16","cited_by_count":134,"area":null},{"id":"2106.09701","title":"Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning","created":"2021-06-17","cited_by_count":131,"area":null},{"id":"2203.11473","title":"Federated Class-Incremental Learning","created":"2022-03-22","cited_by_count":127,"area":null},{"id":"2303.10070","title":"A Unified Continual Learning Framework with General Parameter-Efficient Tuning","created":"2023-03-17","cited_by_count":125,"area":null},{"id":"2103.01737","title":"Distilling Causal Effect of Data in Class-Incremental Learning","created":"2021-03-02","cited_by_count":117,"area":null},{"id":"2106.06047","title":"Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning","created":"2021-06-10","cited_by_count":111,"area":null},{"id":"2303.06614","title":"Synthetic Experience Replay","created":"2023-03-12","cited_by_count":101,"area":null},{"id":"2406.04836","title":"Revisiting Catastrophic Forgetting in Large Language Model Tuning","created":"2024-06-07","cited_by_count":99,"area":null},{"id":"2103.06342","title":"Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations","created":"2021-03-10","cited_by_count":96,"area":null},{"id":"2112.02706","title":"Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning","created":"2021-12-05","cited_by_count":91,"area":null},{"id":"2211.14238","title":"Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time","created":"2022-11-25","cited_by_count":90,"area":null},{"id":"2104.05489","title":"Continual Learning for Text Classification with Information Disentanglement Based Regularization","created":"2021-04-12","cited_by_count":86,"area":null},{"id":"2106.06333","title":"Invariant Information Bottleneck for Domain Generalization","created":"2021-06-11","cited_by_count":86,"area":null},{"id":"2308.01508","title":"Circumventing Concept Erasure Methods For Text-to-Image Generative Models","created":"2023-08-03","cited_by_count":85,"area":null},{"id":"2108.03673","title":"RECALL: Replay-based Continual Learning in Semantic Segmentation","created":"2021-08-08","cited_by_count":83,"area":null},{"id":"2211.12701","title":"Continual Learning of Natural Language Processing Tasks: A Survey","created":"2022-11-23","cited_by_count":83,"area":null},{"id":"2202.02931","title":"TRGP: Trust Region Gradient Projection for Continual Learning","created":"2022-02-07","cited_by_count":82,"area":null},{"id":"2202.06592","title":"Memory Replay with Data Compression for Continual Learning","created":"2022-02-14","cited_by_count":82,"area":null},{"id":"2112.10017","title":"Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks","created":"2021-12-18","cited_by_count":81,"area":null},{"id":"2205.09588","title":"How catastrophic can catastrophic forgetting be in linear regression?","created":"2022-05-19","cited_by_count":81,"area":null},{"id":"2211.02633","title":"A Theoretical Study on Solving Continual Learning","created":"2022-11-04","cited_by_count":80,"area":null},{"id":"2204.07513","title":"Synthesizing Informative Training Samples with GAN","created":"2022-04-15","cited_by_count":77,"area":null},{"id":"2403.05175","title":"Continual Learning and Catastrophic Forgetting","created":"2024-03-08","cited_by_count":77,"area":null},{"id":"2104.07446","title":"Rehearsal revealed: The limits and merits of revisiting samples in continual learning","created":"2021-04-15","cited_by_count":76,"area":null},{"id":"2110.12187","title":"AFEC: Active Forgetting of Negative Transfer in Continual Learning","created":"2021-10-23","cited_by_count":73,"area":null},{"id":"2104.04132","title":"Replay in Deep Learning: Current Approaches and Missing Biological Elements","created":"2021-04-01","cited_by_count":72,"area":null},{"id":"2110.04593","title":"Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning","created":"2021-10-09","cited_by_count":72,"area":null},{"id":"2108.09020","title":"Online Continual Learning with Natural Distribution Shifts: An Empirical Study with Visual Data","created":"2021-08-20","cited_by_count":69,"area":null},{"id":"2307.09218","title":"A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning","created":"2023-07-16","cited_by_count":69,"area":null},{"id":"2101.00407","title":"ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning","created":"2021-01-02","cited_by_count":68,"area":null},{"id":"2110.10031","title":"Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference","created":"2021-10-19","cited_by_count":67,"area":null},{"id":"2301.05792","title":"RMM: Reinforced Memory Management for Class-Incremental Learning","created":"2023-01-14","cited_by_count":66,"area":null},{"id":"2210.03114","title":"CLIP model is an Efficient Continual Learner","created":"2022-10-06","cited_by_count":65,"area":null},{"id":"2303.06937","title":"TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation","created":"2023-03-13","cited_by_count":65,"area":null},{"id":"2104.13417","title":"Towards Fair Federated Learning with Zero-Shot Data Augmentation","created":"2021-04-27","cited_by_count":64,"area":null},{"id":"2110.11526","title":"Wide Neural Networks Forget Less Catastrophically","created":"2021-10-21","cited_by_count":64,"area":null},{"id":"2406.06391","title":"Towards Lifelong Learning of Large Language Models: A Survey","created":"2024-06-10","cited_by_count":64,"area":null},{"id":"2207.09248","title":"Don't Stop Learning: Towards Continual Learning for the CLIP Model","created":"2022-07-19","cited_by_count":61,"area":null},{"id":"2409.07431","title":"Synthetic continued pretraining","created":"2024-09-11","cited_by_count":60,"area":null},{"id":"2103.00991","title":"Few-Shot Lifelong Learning","created":"2021-03-01","cited_by_count":59,"area":null},{"id":"2203.13104","title":"R-DFCIL: Relation-Guided Representation Learning for Data-Free Class Incremental Learning","created":"2022-03-24","cited_by_count":59,"area":null},{"id":"2205.14922","title":"ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection","created":"2022-05-30","cited_by_count":57,"area":null},{"id":"2304.00008","title":"On the Creativity of Large Language Models","created":"2023-03-27","cited_by_count":57,"area":null},{"id":"2105.12374","title":"Continual Learning for Real-World Autonomous Systems: Algorithms, Challenges and Frameworks","created":"2021-05-26","cited_by_count":56,"area":null},{"id":"2109.11369","title":"Recent Advances of Continual Learning in Computer Vision: An Overview","created":"2021-09-23","cited_by_count":55,"area":null},{"id":"2302.00624","title":"Open-VCLIP: Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization","created":"2023-02-01","cited_by_count":55,"area":null},{"id":"2302.13001","title":"Better Generative Replay for Continual Federated Learning","created":"2023-02-25","cited_by_count":55,"area":null},{"id":"2106.03027","title":"Model Zoo: A Growing \"Brain\" That Learns Continually","created":"2021-06-06","cited_by_count":54,"area":null},{"id":"2204.08817","title":"An Efficient Domain-Incremental Learning Approach to Drive in All Weather Conditions","created":"2022-04-19","cited_by_count":54,"area":null},{"id":"2302.00903","title":"No One Left Behind: Real-World Federated Class-Incremental Learning","created":"2023-02-02","cited_by_count":53,"area":null},{"id":"2312.16475","title":"Federated Continual Learning via Knowledge Fusion: A Survey","created":"2023-12-27","cited_by_count":53,"area":null},{"id":"2403.18886","title":"Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning","created":"2024-03-27","cited_by_count":53,"area":null},{"id":"2105.07561","title":"Layerwise Optimization by Gradient Decomposition for Continual Learning","created":"2021-05-17","cited_by_count":51,"area":null},{"id":"2103.13558","title":"Efficient Feature Transformations for Discriminative and Generative Continual Learning","created":"2021-03-25","cited_by_count":50,"area":null},{"id":"2401.03379","title":"Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy","created":"2024-01-07","cited_by_count":50,"area":null},{"id":"2110.00296","title":"Powerpropagation: A sparsity inducing weight reparameterisation","created":"2021-10-01","cited_by_count":49,"area":null},{"id":"2302.01047","title":"Real-Time Evaluation in Online Continual Learning: A New Hope","created":"2023-02-02","cited_by_count":47,"area":null},{"id":"2402.02769","title":"Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate","created":"2024-02-05","cited_by_count":47,"area":null},{"id":"2106.08085","title":"Natural continual learning: success is a journey, not (just) a destination","created":"2021-06-15","cited_by_count":46,"area":null},{"id":"2112.03271","title":"Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification Tasks","created":"2021-12-06","cited_by_count":46,"area":null},{"id":"2202.00275","title":"Architecture Matters in Continual Learning","created":"2022-02-01","cited_by_count":46,"area":null},{"id":"2203.13611","title":"Class-Incremental Learning for Action Recognition in Videos","created":"2022-03-25","cited_by_count":46,"area":null},{"id":"2103.01133","title":"Posterior Meta-Replay for Continual Learning","created":"2021-03-01","cited_by_count":45,"area":null},{"id":"2205.05467","title":"A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials","created":"2022-05-11","cited_by_count":45,"area":null},{"id":"2212.04842","title":"PIVOT: Prompting for Video Continual Learning","created":"2022-12-09","cited_by_count":45,"area":null},{"id":"2211.15969","title":"Isolation and Impartial Aggregation: A Paradigm of Incremental Learning without Interference","created":"2022-11-29","cited_by_count":44,"area":null},{"id":"2311.13534","title":"LM-Cocktail: Resilient Tuning of Language Models via Model Merging","created":"2023-11-22","cited_by_count":44,"area":null},{"id":"2106.02940","title":"Same State, Different Task: Continual Reinforcement Learning without Interference","created":"2021-06-05","cited_by_count":43,"area":null},{"id":"2305.15076","title":"Meta-Learning Online Adaptation of Language Models","created":"2023-05-24","cited_by_count":43,"area":null},{"id":"2307.01163","title":"Improving Language Plasticity via Pretraining with Active Forgetting","created":"2023-07-03","cited_by_count":43,"area":null},{"id":"2308.14991","title":"Incorporating Neuro-Inspired Adaptability for Continual Learning in Artificial Intelligence","created":"2023-08-29","cited_by_count":43,"area":null},{"id":"2311.07784","title":"A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks","created":"2023-11-13","cited_by_count":41,"area":null},{"id":"2101.04904","title":"EEC: Learning to Encode and Regenerate Images for Continual Learning","created":"2021-01-13","cited_by_count":40,"area":null},{"id":"2306.14775","title":"Parameter-Level Soft-Masking for Continual Learning","created":"2023-06-26","cited_by_count":40,"area":null},{"id":"2104.10093","title":"Class-Incremental Learning with Generative Classifiers","created":"2021-04-20","cited_by_count":39,"area":null},{"id":"2112.01882","title":"Incremental Learning in Semantic Segmentation from Image Labels","created":"2021-12-03","cited_by_count":39,"area":null},{"id":"2206.09117","title":"NISPA: Neuro-Inspired Stability-Plasticity Adaptation for Continual Learning in Sparse Networks","created":"2022-06-18","cited_by_count":39,"area":null},{"id":"2208.11148","title":"Multi-domain Learning for Updating Face Anti-spoofing Models","created":"2022-08-23","cited_by_count":39,"area":null}],"next_cursor":"100"}