{"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/clues-before-answers-generation-enhanced","title":"Clues Before Answers: Generation-Enhanced Multiple-Choice QA","arxiv_id":"2205.00274","date":"2022-04-30","proceeding":"NAACL 2022 7","authors":["Zixian Huang","Ao Wu","Jiaying Zhou","Yu Gu","Yue Zhao","Gong Cheng"],"abstract":"A trending paradigm for multiple-choice question answering (MCQA) is using a text-to-text framework. By unifying data in different tasks into a single text-to-text format, it trains a generative encoder-decoder model which is both powerful and universal. However, a side effect of twisting a generation target to fit the classification nature of MCQA is the under-utilization of the decoder and the knowledge that can be decoded. To exploit the generation capability and underlying knowledge of a pre-trained encoder-decoder model, in this paper, we propose a generation-enhanced MCQA model named GenMC. It generates a clue from the question and then leverages the clue to enhance a reader for MCQA. It outperforms text-to-text models on multiple MCQA datasets.","url_abs":"https://arxiv.org/abs/2205.00274v1","url_pdf":"https://arxiv.org/pdf/2205.00274v1.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":"clues-before-answers-generation-enhanced","repo_url":"https://github.com/nju-websoft/genmc","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"multiple-choice-qa","task_name":"Multiple Choice Question Answering (MCQA)"},{"task_slug":"multiple-choice","task_name":"Multiple-choice"},{"task_slug":"question-answering","task_name":"Question Answering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/question-answering-on-openbookqa","task":"Question Answering","dataset":"OpenBookQA","model":"GenMC 11B","rank_in_archive_order":10,"of":45,"metrics":{"Accuracy":"89.8"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2205.00274","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2205.00274"}},"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":"deterministic:regex_extraction","url":"https://github.com/nju-websoft/GenMC","reach":null}],"summary":{"ran":4,"ran_honours":1,"unverified":6},"by_repo_kind":{"official":{"samples":11,"ran":5,"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":"9d9d13aefaa0121e","entry":"BertIntermediate","repo":"nju-websoft/GenMC","repo_kind":"official","path":"model/modeling_genmc.py","file_url":"https://github.com/nju-websoft/GenMC/blob/HEAD/model/modeling_genmc.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"9d9d13aefaa0121e"}},{"code_sha256_prefix":"6a50fa25bd29286f","entry":"BertSelfAttention","repo":"nju-websoft/GenMC","repo_kind":"official","path":"model/modeling_genmc.py","file_url":"https://github.com/nju-websoft/GenMC/blob/HEAD/model/modeling_genmc.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"6a50fa25bd29286f"}},{"code_sha256_prefix":"c6411bfe6a205d2c","entry":"DPDALayear","repo":"nju-websoft/GenMC","repo_kind":"official","path":"model/modeling_genmc.py","file_url":"https://github.com/nju-websoft/GenMC/blob/HEAD/model/modeling_genmc.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"c6411bfe6a205d2c"}},{"code_sha256_prefix":"2b423e9207ab7b7e","entry":"SemanticMatch","repo":"nju-websoft/GenMC","repo_kind":"official","path":"model/modeling_genmc.py","file_url":"https://github.com/nju-websoft/GenMC/blob/HEAD/model/modeling_genmc.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"2b423e9207ab7b7e"}},{"code_sha256_prefix":"a8eafe3c0d1e9892","entry":"gelu","repo":"nju-websoft/GenMC","repo_kind":"official","path":"model/modeling_genmc.py","file_url":"https://github.com/nju-websoft/GenMC/blob/HEAD/model/modeling_genmc.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"a8eafe3c0d1e9892"}},{"code_sha256_prefix":"7ccd797d6076b7bf","entry":"BertAttention","repo":"nju-websoft/GenMC","repo_kind":"official","path":"model/modeling_genmc.py","file_url":"https://github.com/nju-websoft/GenMC/blob/HEAD/model/modeling_genmc.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"7ccd797d6076b7bf"}},{"code_sha256_prefix":"f2960095c4691870","entry":"BertEncoder","repo":"nju-websoft/GenMC","repo_kind":"official","path":"model/modeling_genmc.py","file_url":"https://github.com/nju-websoft/GenMC/blob/HEAD/model/modeling_genmc.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"f2960095c4691870"}},{"code_sha256_prefix":"a9386d3eabfcc480","entry":"BertLayer","repo":"nju-websoft/GenMC","repo_kind":"official","path":"model/modeling_genmc.py","file_url":"https://github.com/nju-websoft/GenMC/blob/HEAD/model/modeling_genmc.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"a9386d3eabfcc480"}},{"code_sha256_prefix":"02ba0bdc7fc80e5a","entry":"Config","repo":"nju-websoft/GenMC","repo_kind":"official","path":"model/modeling_genmc.py","file_url":"https://github.com/nju-websoft/GenMC/blob/HEAD/model/modeling_genmc.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"02ba0bdc7fc80e5a"}},{"code_sha256_prefix":"aff1ad254055ad43","entry":"GenMC","repo":"nju-websoft/GenMC","repo_kind":"official","path":"model/modeling_genmc.py","file_url":"https://github.com/nju-websoft/GenMC/blob/HEAD/model/modeling_genmc.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"aff1ad254055ad43"}},{"code_sha256_prefix":"01622174ba8738f7","entry":"MyTransformer","repo":"nju-websoft/GenMC","repo_kind":"official","path":"model/modeling_genmc.py","file_url":"https://github.com/nju-websoft/GenMC/blob/HEAD/model/modeling_genmc.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"01622174ba8738f7"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}