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cs.CL2026
DeepInstructor: An Agentic AI Instructor for Experience-Driven Idea Evaluation
Rongcan Pei, Fang Guo, Qinglin Qi +7
As automated scientific discovery advances, Large Language Models (LLMs) can now generate research ideas at an unprecedented scale, shifting the bottleneck from idea generation to…
cs.CL2026
When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors
Yuqing Yang, Qi Zhu, Zhen Han +5
While large language models (LLMs) perform well on table tasks, they still make data referencing errors (DREs), i.e., incorrectly citing or omitting table values, despite understan…