BridgeAlign: Bridging Preference Alignment for Humanities and Social Sciences
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[2607.27366] BridgeAlign: Bridging Preference Alignment for Humanities and Social Sciences Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Computation and Language arXiv:2607.27366 (cs) [Submitted on 29 Jul 2026 ( v1 ), last revised 14 Aug 2026 (this version, v2)] Title: BridgeAlign: Bridging Preference Alignment for Humanities and Social Sciences Authors: Ru Peng , Haokai Xu , Xijun Gu , Tianyu Zhao , Zhiting Fan , Yawen Zeng , Yihong Zhuang , Jinyang Zhang , Kexin Yang , Jian Wu , Hao Chen , Junyang Lin , Dayiheng Liu , Junbo Zhao View a PDF of the paper titled BridgeAlign: Bridging Preference Alignment for Humanities and Social Sciences, by Ru Peng and 13 other authors View PDF HTML (experimental) Abstract: While data synthesis for large language models (LLMs) is prevalent, it primarily targets domains with verifiable answers, overlooking open-ended humanities and social sciences (HSS), where nuanced quality judgments matter more than objective correctness. This makes preference alignment a natural paradigm for broad HSS tasks. Yet existing methods are either costly or not tailored to broad HSS disciplines. We thus propose BridgeAlign, among the first preference-alignment pipelines for broad HSS disciplines, with three phases: i) Seed Curation: curating HSS seed documents from web corpora via heuristic/LLM-based filtering and text refinement; ii) Preference Data Synthesis: generating preference triplets via persona-based instruction inversion with Q&A consistency checks; iii) Preference Optimization: moving beyond naive human-vs-model heuristics by first grounding preferences in HSS quality rubric, then generating transitional responses via controlled quality degradation to form near-boundary preference pairs for finer-grained quality discrimination. Aligning over 210k synthetic preference samples, BridgeAlign enables Qwen3-8B to achieve the best average across 17 benchmarks against 11 strong baselines; importantly, leading on both human-preference and knowledge-based capabilities at once, with no trade-off between them, as supported by extensive experiments and contextualized by existing theories. Subjects: Computation and Language (cs.CL) Cite as: arXiv:2607.27366 [cs.CL] (or arXiv:2607.27366v2 [cs.CL] for this version) https://doi.org/10.48550/arXiv.2607.27366 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Ru Peng [ view email ] [v1] Wed, 29 Jul 2026 18:22:50 UTC (3,487 KB) [v2] Fri, 14 Aug 2026 18:37:38 UTC (3,486 KB) Full-text links: Access Paper: View a PDF of the paper titled BridgeAlign: Bridging Preference Alignment for Humanities and Social Sciences, by Ru Peng and 13 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.CL < prev | next > new | recent | 2026-07 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from
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