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cs.CL2026
Are Large Language Models Reliable Reviewers? A Benchmark for Error Detection in Financial Documents
Ying He, Zhouhong Gu, Zhecheng Hu +8
Ensuring the accuracy of financial documents is critical for economic analysis, regulatory compliance, and corporate decision-making. Several studies have shown that Large Language…
cs.CL2026
SEIF: Self-Evolving Reinforcement Learning for Instruction Following
Qingyu Ren, Qianyu He, Jiajie Zhu +7
Instruction following is a fundamental capability of large language models (LLMs), yet continuously improving this capability remains challenging. Existing methods typically rely e…