{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/uncovering-selective-state-space-model-s","title":"Uncovering Selective State Space Model's Capabilities in Lifelong Sequential Recommendation","arxiv_id":"2403.16371","date":"2024-03-25","proceeding":null,"authors":["Jiyuan Yang","Yuanzi Li","Jingyu Zhao","Hanbing Wang","Muyang Ma","Jun Ma","Zhaochun Ren","Mengqi Zhang","Xin Xin","Zhumin Chen","Pengjie Ren"],"abstract":"Sequential Recommenders have been widely applied in various online services, aiming to model users' dynamic interests from their sequential interactions. With users increasingly engaging with online platforms, vast amounts of lifelong user behavioral sequences have been generated. However, existing sequential recommender models often struggle to handle such lifelong sequences. The primary challenges stem from computational complexity and the ability to capture long-range dependencies within the sequence. Recently, a state space model featuring a selective mechanism (i.e., Mamba) has emerged. In this work, we investigate the performance of Mamba for lifelong sequential recommendation (i.e., length>=2k). More specifically, we leverage the Mamba block to model lifelong user sequences selectively. We conduct extensive experiments to evaluate the performance of representative sequential recommendation models in the setting of lifelong sequences. Experiments on two real-world datasets demonstrate the superiority of Mamba. We found that RecMamba achieves performance comparable to the representative model while significantly reducing training duration by approximately 70% and memory costs by 80%. Codes and data are available at \\url{https://github.com/nancheng58/RecMamba}.","url_abs":"https://arxiv.org/abs/2403.16371v1","url_pdf":"https://arxiv.org/pdf/2403.16371v1.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":"uncovering-selective-state-space-model-s","repo_url":"https://github.com/nancheng58/recmamba","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"2k","task_name":"2k"},{"task_slug":"mamba","task_name":"Mamba"},{"task_slug":"sequential-recommendation","task_name":"Sequential Recommendation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2403.16371","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.16371"}},"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. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/nancheng58/recmamba","reach":null}],"summary":{"ran_draft_wrong":1,"ran":1,"ran_honours":1,"unverified":2},"by_repo_kind":{"official":{"samples":5,"ran":3,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":5,"samples":[{"code_sha256_prefix":"c66ba29ebef33103","entry":"clones","repo":"nancheng58/recmamba","repo_kind":"official","path":"model.py","file_url":"https://github.com/nancheng58/recmamba/blob/HEAD/model.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"c66ba29ebef33103"}},{"code_sha256_prefix":"f21420da9770e8dd","entry":"data_partition","repo":"nancheng58/recmamba","repo_kind":"official","path":"utils.py","file_url":"https://github.com/nancheng58/recmamba/blob/HEAD/utils.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"f21420da9770e8dd"}},{"code_sha256_prefix":"13e1db5681123f3a","entry":"random_neq","repo":"nancheng58/recmamba","repo_kind":"official","path":"utils.py","file_url":"https://github.com/nancheng58/recmamba/blob/HEAD/utils.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"13e1db5681123f3a"}},{"code_sha256_prefix":"6f5ecc125f252b2a","entry":"linrec","repo":"nancheng58/recmamba","repo_kind":"official","path":"model.py","file_url":"https://github.com/nancheng58/recmamba/blob/HEAD/model.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"6f5ecc125f252b2a"}},{"code_sha256_prefix":"ea2f06927b8d7ee4","entry":"sample_function","repo":"nancheng58/recmamba","repo_kind":"official","path":"utils.py","file_url":"https://github.com/nancheng58/recmamba/blob/HEAD/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"ea2f06927b8d7ee4"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}