BridgeAlign: Bridging Preference Alignment for Humanities and Social Sciences
Quick Answer
BridgeAlign introduces a novel preference-alignment pipeline for humanities and social sciences, enhancing Qwen3-8B's performance across 17 benchmarks.
Quick Take
It curates over 210k synthetic preference samples, achieving superior human-preference and knowledge-based capabilities without trade-offs, addressing the need for nuanced quality judgments in open-ended domains.
Key Points
- BridgeAlign consists of three phases: Seed Curation, Preference Data Synthesis, and Preference Optimization.
- The model aligns over 210k synthetic preference samples, setting new benchmarks in HSS tasks.
- It achieves the best average performance against 11 strong baselines across 17 benchmarks.
- No trade-off exists between human-preference and knowledge-based capabilities in the results.
- The approach addresses the unique challenges of quality judgments in humanities and social sciences.
Paper Resources
Source Excerpt
While data synthesis for (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 di
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