HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs
Quick Answer
HSS-Synth introduces a novel data synthesis pipeline for humanities and social sciences, generating 237k high-quality instruction-tuning samples that outperform 14 leading baselines across 16 benchmarks.
Quick Take
The fine-tuned Qwen3-8B-Base sets a new state-of-the-art in performance, enhancing human preference and knowledge capabilities without performance fluctuations.
Key Points
- HSS-Synth covers 14 mainstream fields in humanities and social sciences.
- The pipeline uses multi-step filtering and text refinement for seed document construction.
- It employs teacher-forced answering to anchor semantics and reduce hallucinations.
- The generated samples outperform existing models on 16 benchmarks.
- Code for HSS-Synth is publicly available for further research.
Paper Resources
Source Excerpt
High-quality, diverse data are vital for (LLMs) but remain scarce and costly. Data synthesis is a viable alternative and succeeds on closed tasks, yet the humanities and social sciences (HSS) are overlooked, and their open-ended nature makes synthesis challenging. Moving beyond prior capability-centric, fragmented attempts, we adopt a subject-centric paradigm, define the first HSS domain system covering 14 mainstream fields, and introduce HSS-Synth, the first data synthesis
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