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Home/Authors/Zonglin Yang

Zonglin Yang

1 indexed paper

Recent (6 mo)
1
With code
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Publications per year

1
26

Top categories

NLP×1AI×1Comp. Eng.×1HCI×1

Frequent co-authors

Hongran An1×

Research Timeline

2026
MOOSE-Copilot: A Web-Based Interactive Assistant for Unified Exploratory and Fine-Grained Scientific Hypothesis Discovery

MOOSE-Copilot is a novel web-based framework that unifies scientific hypothesis discovery by formalizing human-AI interaction, significantly improving performance over autonomous LLM baselines.

Highlighted terms show continued research focus across papers

Papers

cs.CLcs.AIcs.CERecentMay 28, 2026

MOOSE-Copilot: A Web-Based Interactive Assistant for Unified Exploratory and Fine-Grained Scientific Hypothesis Discovery

Hongran An, Zonglin Yang

MOOSE-Copilot is a novel web-based framework that unifies scientific hypothesis discovery by formalizing human-AI interaction, significantly improving performance over autonomous LLM baselines.

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