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cs.CL2026
Improved Evidence Extraction and Metrics for Document Inconsistency Detection with LLMs
Nelvin Tan, Yaowen Zhang, James Asikin Cheung +3
Large language models (LLMs) are becoming useful in many domains due to their impressive abilities that arise from large training datasets and large model sizes. However, research…
cs.CL2025
Does Using Counterfactual Help LLMs Explain Textual Importance in Classification?
Nelvin Tan, James Asikin Cheung, Yu-Ching Shih +2
Large language models (LLMs) are becoming useful in many domains due to their impressive abilities that arise from large training datasets and large model sizes. More recently, the…
cs.CL2025
Improved LLM Agents for Financial Document Question Answering
Nelvin Tan, Zian Seng, Liang Zhang +3
Large language models (LLMs) have shown impressive capabilities on numerous natural language processing tasks. However, LLMs still struggle with numerical question answering for fi…