1 citations · 1 across the 4 of their papers we have counts for
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BalanceRAG: Joint Risk Calibration for Cascaded Retrieval-Augmented Generation
Zijun Jia, Yuanchang Ye, Sen Jia +6
Large language models (LLMs) can enhance factuality via retrieval-augmented generation (RAG), but applying RAG to every query is unnecessary when the model-only answer is reliable.…
Set-Valued Prediction for Large Language Models with Feasibility-Aware Coverage Guarantees
Ye Li, Anqi Hu, Yuanchang Ye +3
Large language models (LLMs) inherently operate over a large generation space, yet conventional usage typically reports the most likely generation (MLG) as a point prediction, whic…
Conformal P-Value in Multiple-Choice Question Answering Tasks with Provable Risk Control
Yuanchang Ye
This study introduces a significance testing-enhanced conformal prediction (CP) framework to improve trustworthiness of large language models (LLMs) in multiple-choice question ans…
Data-Driven Calibration of Prediction Sets in Large Vision-Language Models Based on Inductive Conformal Prediction
Yuanchang Ye, Weiyan Wen
This study addresses the critical challenge of hallucination mitigation in Large Vision-Language Models (LVLMs) for Visual Question Answering (VQA) tasks through a Split Conformal…