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cs.CL2026
Rubrics on Trial: Evolving Rubrics from a Single Query via Synthetic Pairwise Evidence
Haocheng Yang, Licheng Pan, Xiaoxi Li +5
Rubrics provide structured, fine-grained signals for training and evaluating large language models (LLMs). Yet reliable query-specific rubrics are difficult to construct. Existing…
cs.CL2025
Mitigating Hidden Confounding by Progressive Confounder Imputation via Large Language Models
Hao Yang, Haoxuan Li, Luyu Chen +3
Hidden confounding remains a central challenge in estimating treatment effects from observational data, as unobserved variables can lead to biased causal estimates. While recent wo…