{"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/social-sycophancy-a-broader-understanding-of","title":"Social Sycophancy: A Broader Understanding of LLM Sycophancy","arxiv_id":"2505.13995","date":"2025-05-20","proceeding":null,"authors":["Myra Cheng","Sunny Yu","Cinoo Lee","Pranav Khadpe","Lujain Ibrahim","Dan Jurafsky"],"abstract":"A serious risk to the safety and utility of LLMs is sycophancy, i.e., excessive agreement with and flattery of the user. Yet existing work focuses on only one aspect of sycophancy: agreement with users' explicitly stated beliefs that can be compared to a ground truth. This overlooks forms of sycophancy that arise in ambiguous contexts such as advice and support-seeking, where there is no clear ground truth, yet sycophancy can reinforce harmful implicit assumptions, beliefs, or actions. To address this gap, we introduce a richer theory of social sycophancy in LLMs, characterizing sycophancy as the excessive preservation of a user's face (the positive self-image a person seeks to maintain in an interaction). We present ELEPHANT, a framework for evaluating social sycophancy across five face-preserving behaviors (emotional validation, moral endorsement, indirect language, indirect action, and accepting framing) on two datasets: open-ended questions (OEQ) and Reddit's r/AmITheAsshole (AITA). Across eight models, we show that LLMs consistently exhibit high rates of social sycophancy: on OEQ, they preserve face 47% more than humans, and on AITA, they affirm behavior deemed inappropriate by crowdsourced human judgments in 42% of cases. We further show that social sycophancy is rewarded in preference datasets and is not easily mitigated. Our work provides theoretical grounding and empirical tools (datasets and code) for understanding and addressing this under-recognized but consequential issue.","url_abs":"https://arxiv.org/abs/2505.13995v1","url_pdf":"https://arxiv.org/pdf/2505.13995v1.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":"social-sycophancy-a-broader-understanding-of","repo_url":"https://github.com/myracheng/elephant","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2505.13995","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2505.13995"}},"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/myracheng/elephant","reach":null}],"summary":{"ran_draft_wrong":2},"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":"e525e4a3e64d01a6","entry":"compute_rates","repo":"myracheng/elephant","repo_kind":"official","path":"moral_sycophancy_scorer.py","file_url":"https://github.com/myracheng/elephant/blob/HEAD/moral_sycophancy_scorer.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":"CC0-1.0","inline_ok":true,"mcp_get_code":{"code_sha256":"e525e4a3e64d01a6"}},{"code_sha256_prefix":"01384b0681810072","entry":"create_prompt","repo":"myracheng/elephant","repo_kind":"official","path":"sycophancy_scorers.py","file_url":"https://github.com/myracheng/elephant/blob/HEAD/sycophancy_scorers.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":"CC0-1.0","inline_ok":true,"mcp_get_code":{"code_sha256":"01384b0681810072"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}