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This work provides a\nsystematic categorization of the scenarios and evaluates them within a\nconsistent framework including strong baselines and state-of-the-art methods.\nThe results provide an understanding of the relative difficulty of the\nscenarios and that simple baselines (Adagrad, L2 regularization, and naive\nrehearsal strategies) can surprisingly achieve similar performance to current\nmainstream methods. We conclude with several suggestions for creating harder\nevaluation scenarios and future research directions. The code is available at\nhttps://github.com/GT-RIPL/Continual-Learning-Benchmark","url_abs":"http://arxiv.org/abs/1810.12488v4","url_pdf":"http://arxiv.org/pdf/1810.12488v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"re-evaluating-continual-learning-scenarios-a","repo_url":"https://github.com/GT-RIPL/Continual-Learning-Benchmark","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"re-evaluating-continual-learning-scenarios-a","repo_url":"https://github.com/MehdiAbbanaBennani/continual-learning-ogdplus","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"re-evaluating-continual-learning-scenarios-a","repo_url":"https://github.com/lukinio/CL_CWAE","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"continual-learning","task_name":"Continual Learning"},{"task_slug":"l2-regularization","task_name":"L2 Regularization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1810.12488","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1810.12488"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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