{"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/weakly-supervised-scientific-document","title":"Weakly-Supervised Scientific Document Classification via Retrieval-Augmented Multi-Stage Training","arxiv_id":"2306.07193","date":"2023-06-12","proceeding":null,"authors":["ran Xu","Yue Yu","Joyce C. Ho","Carl Yang"],"abstract":"Scientific document classification is a critical task for a wide range of applications, but the cost of obtaining massive amounts of human-labeled data can be prohibitive. To address this challenge, we propose a weakly-supervised approach for scientific document classification using label names only. In scientific domains, label names often include domain-specific concepts that may not appear in the document corpus, making it difficult to match labels and documents precisely. To tackle this issue, we propose WANDER, which leverages dense retrieval to perform matching in the embedding space to capture the semantics of label names. We further design the label name expansion module to enrich the label name representations. Lastly, a self-training step is used to refine the predictions. The experiments on three datasets show that WANDER outperforms the best baseline by 11.9% on average. Our code will be published at https://github.com/ritaranx/wander.","url_abs":"https://arxiv.org/abs/2306.07193v1","url_pdf":"https://arxiv.org/pdf/2306.07193v1.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":"weakly-supervised-scientific-document","repo_url":"https://github.com/ritaranx/wander","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"document-classification","task_name":"Document Classification"},{"task_slug":"retrieval","task_name":"Retrieval"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2306.07193","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.07193"}},"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/ritaranx/wander","reach":null}],"summary":{"ran_draft_wrong":1,"ran_honours":1},"by_repo_kind":{"official":{"samples":2,"ran":2,"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":0,"samples":[{"code_sha256_prefix":"9dc9d7b5719a1ecc","entry":"load_pred_data","repo":"ritaranx/wander","repo_kind":"official","path":"dense_retrieval.py","file_url":"https://github.com/ritaranx/wander/blob/HEAD/dense_retrieval.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":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"9dc9d7b5719a1ecc"}},{"code_sha256_prefix":"0450e58f35f90bdf","entry":"tensor_to_numpy","repo":"ritaranx/wander","repo_kind":"official","path":"keyword_expansion.py","file_url":"https://github.com/ritaranx/wander/blob/HEAD/keyword_expansion.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"0450e58f35f90bdf"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}