{"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/semireward-a-general-reward-model-for-semi","title":"SemiReward: A General Reward Model for Semi-supervised Learning","arxiv_id":"2310.03013","date":"2023-10-04","proceeding":null,"authors":["Siyuan Li","Weiyang Jin","Zedong Wang","Fang Wu","Zicheng Liu","Cheng Tan","Stan Z. Li"],"abstract":"Semi-supervised learning (SSL) has witnessed great progress with various improvements in the self-training framework with pseudo labeling. The main challenge is how to distinguish high-quality pseudo labels against the confirmation bias. However, existing pseudo-label selection strategies are limited to pre-defined schemes or complex hand-crafted policies specially designed for classification, failing to achieve high-quality labels, fast convergence, and task versatility simultaneously. To these ends, we propose a Semi-supervised Reward framework (SemiReward) that predicts reward scores to evaluate and filter out high-quality pseudo labels, which is pluggable to mainstream SSL methods in wide task types and scenarios. To mitigate confirmation bias, SemiReward is trained online in two stages with a generator model and subsampling strategy. With classification and regression tasks on 13 standard SSL benchmarks across three modalities, extensive experiments verify that SemiReward achieves significant performance gains and faster convergence speeds upon Pseudo Label, FlexMatch, and Free/SoftMatch. Code and models are available at https://github.com/Westlake-AI/SemiReward.","url_abs":"https://arxiv.org/abs/2310.03013v2","url_pdf":"https://arxiv.org/pdf/2310.03013v2.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":"semireward-a-general-reward-model-for-semi","repo_url":"https://github.com/Westlake-AI/SemiReward","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"few-shot-image-classification","task_name":"Few-Shot Image Classification"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"pseudo-label","task_name":"Pseudo Label"},{"task_slug":"semi-supervised-image-classification","task_name":"Semi-Supervised Image Classification"},{"task_slug":"semi-supervised-text-classification-1","task_name":"Semi-Supervised Text Classification"},{"task_slug":"semi-supervised-audio-classification","task_name":"Semi-supervised Audio Classification"},{"task_slug":"transfer-learning","task_name":"Transfer Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/semi-supervised-image-classification-on-cifar-8","task":"Semi-Supervised Image Classification","dataset":"CIFAR-100, 400 Labels","model":"SemiReward","rank_in_archive_order":1,"of":21,"metrics":{"Percentage error":"15.62"},"uses_additional_data":false},{"leaderboard":"/sota/semi-supervised-image-classification-on-1","task":"Semi-Supervised Image Classification","dataset":"ImageNet - 1% labeled data","model":"SemiReward","rank_in_archive_order":39,"of":65,"metrics":{"Top 1 Accuracy":"59.64%"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2310.03013","atlas_url":"https://app.syntology.ai/?focus=2310.03013","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.03013"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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/Westlake-AI/SemiReward","reach":null}],"summary":{"ran":1,"ran_draft_wrong":2,"ran_honours":1,"unverified":1},"by_repo_kind":{"official":{"samples":4,"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":1,"samples":[{"code_sha256_prefix":"f49f78672594e734","entry":"Rewarder","repo":"Westlake-AI/SemiReward","repo_kind":"official","path":"semilearn/algorithms/semireward/semireward.py","file_url":"https://github.com/Westlake-AI/SemiReward/blob/HEAD/semilearn/algorithms/semireward/semireward.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"f49f78672594e734"}},{"code_sha256_prefix":"c416c897b374d349","entry":"add_gaussian_noise","repo":"Westlake-AI/SemiReward","repo_kind":"official","path":"semilearn/algorithms/semireward/semireward.py","file_url":"https://github.com/Westlake-AI/SemiReward/blob/HEAD/semilearn/algorithms/semireward/semireward.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"c416c897b374d349"}},{"code_sha256_prefix":"296f0456da95f726","entry":"cosine_similarity_n","repo":"Westlake-AI/SemiReward","repo_kind":"official","path":"semilearn/algorithms/semireward/semireward.py","file_url":"https://github.com/Westlake-AI/SemiReward/blob/HEAD/semilearn/algorithms/semireward/semireward.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"296f0456da95f726"}},{"code_sha256_prefix":"d7a641a66e8832f8","entry":"label_dim","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"d7a641a66e8832f8"}},{"code_sha256_prefix":"26c6cc5d552ca423","entry":"label_dim","repo":"Westlake-AI/SemiReward","repo_kind":"official","path":"semilearn/algorithms/semireward/semireward.py","file_url":"https://github.com/Westlake-AI/SemiReward/blob/HEAD/semilearn/algorithms/semireward/semireward.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":"HONOURS","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"26c6cc5d552ca423"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}