{"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/decomposed-prompt-tuning-via-low-rank","title":"Decomposed Prompt Tuning via Low-Rank Reparameterization","arxiv_id":"2310.10094","date":"2023-10-16","proceeding":null,"authors":["Yao Xiao","Lu Xu","Jiaxi Li","Wei Lu","XiaoLi Li"],"abstract":"While prompt tuning approaches have achieved competitive performance with high efficiency, we observe that they invariably employ the same initialization process, wherein the soft prompt is either randomly initialized or derived from an existing embedding vocabulary. In contrast to these conventional methods, this study aims to investigate an alternative way to derive soft prompt. Our empirical studies show that the soft prompt typically exhibits a low intrinsic rank characteristic. With such observations, we propose decomposed prompt tuning, a novel approach that utilizes low-rank matrices to initialize the soft prompt. Through the low-rank reparameterization, our method significantly reduces the number of trainable parameters while maintaining effectiveness. Experimental results on the SuperGLUE benchmark in both high-resource and low-resource scenarios demonstrate the effectiveness of the proposed method.","url_abs":"https://arxiv.org/abs/2310.10094v1","url_pdf":"https://arxiv.org/pdf/2310.10094v1.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":"decomposed-prompt-tuning-via-low-rank","repo_url":"https://github.com/xyaoooo/dpt","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2310.10094","atlas_url":"https://app.syntology.ai/?focus=2310.10094","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.10094"}},"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/xyaoooo/dpt","reach":{"status":"ok"}}],"summary":{"ran":7,"ran_violates":2},"by_repo_kind":{"official":{"samples":9,"ran":9,"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":9,"samples":[{"code_sha256_prefix":"6872d2270ac0fcce","entry":"accuracy","repo":"xyaoooo/dpt","repo_kind":"official","path":"metrics.py","file_url":"https://github.com/xyaoooo/dpt/blob/HEAD/metrics.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"6872d2270ac0fcce"}},{"code_sha256_prefix":"c6fe4e5139f2af4c","entry":"average_multi_task","repo":"xyaoooo/dpt","repo_kind":"official","path":"metrics.py","file_url":"https://github.com/xyaoooo/dpt/blob/HEAD/metrics.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":"c6fe4e5139f2af4c"}},{"code_sha256_prefix":"9dfac665ee4f58c2","entry":"dataset_sampling","repo":"xyaoooo/dpt","repo_kind":"official","path":"utils.py","file_url":"https://github.com/xyaoooo/dpt/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":"9dfac665ee4f58c2"}},{"code_sha256_prefix":"6ca2103b615cffe9","entry":"generate_sharing_matrix","repo":"xyaoooo/dpt","repo_kind":"official","path":"utils.py","file_url":"https://github.com/xyaoooo/dpt/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":"6ca2103b615cffe9"}},{"code_sha256_prefix":"708ca1cba9f2908f","entry":"is_port_in_use","repo":"xyaoooo/dpt","repo_kind":"official","path":"utils.py","file_url":"https://github.com/xyaoooo/dpt/blob/HEAD/utils.py","link_basis":"plan_row","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"708ca1cba9f2908f"}},{"code_sha256_prefix":"f7f2b029a1b6fe03","entry":"multi_task_gain","repo":"xyaoooo/dpt","repo_kind":"official","path":"metrics.py","file_url":"https://github.com/xyaoooo/dpt/blob/HEAD/metrics.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":"f7f2b029a1b6fe03"}},{"code_sha256_prefix":"f94fdeecf0c81e4e","entry":"str2bool","repo":"xyaoooo/dpt","repo_kind":"official","path":"options.py","file_url":"https://github.com/xyaoooo/dpt/blob/HEAD/options.py","link_basis":"plan_row","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"f94fdeecf0c81e4e"}},{"code_sha256_prefix":"f5c7044effdbdf47","entry":"string_to_float","repo":"xyaoooo/dpt","repo_kind":"official","path":"eval_utils.py","file_url":"https://github.com/xyaoooo/dpt/blob/HEAD/eval_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":"f5c7044effdbdf47"}},{"code_sha256_prefix":"2b4d8bb53fc3f929","entry":"wsc_simple","repo":"xyaoooo/dpt","repo_kind":"official","path":"eval_utils.py","file_url":"https://github.com/xyaoooo/dpt/blob/HEAD/eval_utils.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"2b4d8bb53fc3f929"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}