Author

Tianyun Zhong

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Preprint Oct 2026

SCI-AGENT-EXAM: Benchmarking Agents on Scientific Research Tasks

Large language model (LLM) agents are increasingly capable of supporting scientific workflows, but their capabilities across diverse research activities remain difficult to assess systematically. Existing benchmarks often focus on selected scientific capabilities or task types, limiting a comprehensive characterization...

Tian-Yun Zhong, Wei Wang, Jia-Ling Li et al. · 0 citations

#natural language process... Jul 2025

Beyond Isolated Dots: Benchmarking Structured Table Construction as Deep Knowledge Extraction

AOE (Arranged and Organized Extraction), a bilingual benchmark that evaluates LLMs'ability to distill long-form, multi-document inputs into structured tables, is introduced, revealing that structured extraction from long contexts remains a fundamental challenge - an"Area of Effect"(AOE) that impacts all tested systems.

Tian-Yun Zhong, Guozhao Mo, Yan-Jiang Liu et al. · arXiv.org · 0 citations

Jul 2026

Before the Action: Benchmarking LLMs on Prospective Hypothesis Discovery

Results support treating PHD as a distinct target for evaluating how LLMs formulate investigative directions when final conclusions are withheld, with gains for several lower-performing models on HypoArena but regressions for other systems, including a top-performing model.

Tianyun Zhong, Wangyi Jiang, Wei Wang et al. · arXiv.org · 0 citations