{"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/mmlu-pro-evaluating-higher-order-reasoning","title":"MMLU-Pro+: Evaluating Higher-Order Reasoning and Shortcut Learning in LLMs","arxiv_id":"2409.02257","date":"2024-09-03","proceeding":null,"authors":["Saeid Asgari Taghanaki","Aliasgahr Khani","Amir Khasahmadi"],"abstract":"Existing benchmarks for large language models (LLMs) increasingly struggle to differentiate between top-performing models, underscoring the need for more challenging evaluation frameworks. We introduce MMLU-Pro+, an enhanced benchmark building upon MMLU-Pro to assess shortcut learning and higher-order reasoning in LLMs. By incorporating questions with multiple correct answers across diverse domains, MMLU-Pro+ tests LLMs' ability to engage in complex reasoning and resist simplistic problem-solving strategies. Our results show that MMLU-Pro+ maintains MMLU-Pro's difficulty while providing a more rigorous test of model discrimination, particularly in multi-correct answer scenarios. We introduce novel metrics like shortcut selection ratio and correct pair identification ratio, offering deeper insights into model behavior and anchoring bias. Evaluations of six state-of-the-art LLMs reveal significant performance gaps, highlighting variations in reasoning abilities and bias susceptibility. We release the dataset and evaluation codes at \\url{https://github.com/asgsaeid/mmlu-pro-plus}.","url_abs":"https://arxiv.org/abs/2409.02257v3","url_pdf":"https://arxiv.org/pdf/2409.02257v3.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":"mmlu-pro-evaluating-higher-order-reasoning","repo_url":"https://github.com/asgsaeid/mmlu-pro-plus","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"mmlu","task_name":"MMLU"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2409.02257","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2409.02257"}},"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/asgsaeid/mmlu-pro-plus","reach":null}],"summary":{"ran_draft_wrong":2,"unverified":1},"by_repo_kind":{"official":{"samples":3,"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":3,"samples":[{"code_sha256_prefix":"df80a0e9f84176ff","entry":"format_example","repo":"asgsaeid/mmlu-pro-plus","repo_kind":"official","path":"evaluate_from_api.py","file_url":"https://github.com/asgsaeid/mmlu-pro-plus/blob/HEAD/evaluate_from_api.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"df80a0e9f84176ff"}},{"code_sha256_prefix":"d5df2854c95c8fe2","entry":"preprocess","repo":"asgsaeid/mmlu-pro-plus","repo_kind":"official","path":"evaluate_from_api.py","file_url":"https://github.com/asgsaeid/mmlu-pro-plus/blob/HEAD/evaluate_from_api.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":"d5df2854c95c8fe2"}},{"code_sha256_prefix":"e5a8f0fb32623146","entry":"call_api","repo":"asgsaeid/mmlu-pro-plus","repo_kind":"official","path":"evaluate_from_api.py","file_url":"https://github.com/asgsaeid/mmlu-pro-plus/blob/HEAD/evaluate_from_api.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":"e5a8f0fb32623146"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}