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From the 2 of 5 linked papers with an AI index.

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5 papers

cs.CL2026

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs

Ru Peng, Tianyu Zhao, Xijun Gu +9

The paper introduces HSS-Synth, a pipeline that creates high‑quality instruction‑tuning data for large language models in the humanities and social sciences by generating seed docu…

cs.CL2026

BridgeAlign: Bridging Preference Alignment for Humanities and Social Sciences

Ru Peng, Haokai Xu, Xijun Gu +11

BridgeAlign introduces a three-stage pipeline that creates and uses synthetic preference data to align large language models with nuanced quality judgments in humanities and social…

cs.LG2026

FEAT: A Linear-Complexity Foundation Model for Extremely Large Structured Data

Zhenghang Song, Tang Qian, Lu Chen +7

Structured data is widely used in domains such as healthcare, finance, and scientific data management. Recent studies on structured data foundation models (SFMs) aim to support dat…

cs.CL2026

RPDR: A Round-trip Prediction-Based Data Augmentation Framework for Long-Tail Question Answering

Yiming Zhang, Siyue Zhang, Junbo Zhao +1

Long-tail question answering presents significant challenges for large language models (LLMs) due to their limited ability to acquire and accurately recall less common knowledge. R…

cs.CL2025

DataMan: Data Manager for Pre-training Large Language Models

Ru Peng, Kexin Yang, Yawen Zeng +3

The performance emergence of large language models (LLMs) driven by data scaling laws makes the selection of pre-training data increasingly important. However, existing methods rel…