Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/120092
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Language Science and Technology | en_US |
| dc.creator | Feng, Z | en_US |
| dc.creator | Chen, Z | en_US |
| dc.creator | Ma, J | en_US |
| dc.creator | Po, YT | en_US |
| dc.creator | Chersoni, E | en_US |
| dc.creator | Li, B | en_US |
| dc.date.accessioned | 2026-07-22T08:13:08Z | - |
| dc.date.available | 2026-07-22T08:13:08Z | - |
| dc.identifier.isbn | 979-8-89176-390-6 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/120092 | - |
| dc.description | The 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), San Diego, California, United States, July 2-7, 2026 | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Association for Computational Linguistics | en_US |
| dc.rights | ©2026 Association for Computational Linguistics | en_US |
| dc.rights | Licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) | en_US |
| dc.rights | The following publication Feng, Z., Chen, Z., Ma, J., Po, Y. T., Chersoni, E., & Li, B. (2026). Good arguments against the people pleasers: How reasoning Mitigates (yet masks) LLM Sycophancy. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 24536–24570 is available at https://doi.org/10.18653/v1/2026.acl-long.1126. | en_US |
| dc.title | Good arguments against the people pleasers : how reasoning mitigates (yet masks) LLM sycophancy | en_US |
| dc.type | Conference Paper | en_US |
| dc.identifier.spage | 24536 | en_US |
| dc.identifier.epage | 24570 | en_US |
| dc.identifier.doi | 10.18653/v1/2026.acl-long.1126 | en_US |
| dcterms.abstract | Alignment techniques often inadvertently induce sycophancy in LLMs. While prior studies examined this behavior in direct-answer settings, the role of Chain-of-Thought (CoT) reasoning remains underexplored: does it serve as a logical constraint that mitigates sycophancy, or as a tool for post-hoc rationalization that masks it? We evaluate a range of models across objective and subjective tasks to investigate this issue. Results show that reasoning generally reduces sycophancy in final decisions but also masks sycophancy in some samples, where models construct deceptive justifications through logical inconsistencies, calculation errors, and one-sided arguments. Furthermore, LLMs are more prone to sycophancy in subjective tasks and under authority bias. Our mechanistic analysis on three open-source models reveals that the tendency toward sycophancy is dynamic during the reasoning process rather than predetermined at the input stage. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | In 64th Annual Meeting of the Association for Computational Linguistic: Proceedings of the Conference Vol. 1 (Long Papers), p. 24536–24570. Kerrville : Association for Computational Linguistics(ACL), 2026 | en_US |
| dcterms.issued | 2026 | - |
| dc.relation.ispartofbook | Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) | en_US |
| dc.relation.conference | Annual Meeting of the Association for Computational Linguistics | en_US |
| dc.description.validate | 202607 bcwc | en_US |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | a4672 | - |
| dc.identifier.SubFormID | 53570 | - |
| dc.description.fundingSource | Self-funded | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | CC | en_US |
| Appears in Collections: | Conference Paper | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2026.acl-long.1126.pdf | 3.84 MB | Adobe PDF | View/Open |
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