Author

Rongyu Zhang

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Conference Open access Nov 2026

Don’t Guess, Ask Wisely: Benchmarking and Training Proactive Elicitation in Open-Domain LLM Conversations

When user queries are incomplete, large language models should ask targeted questions before committing to an answer, a capability we call proactive elicitation, yet evaluation on real user-assistant queries across seven LLMs (8B to frontier) shows that fewer than 11% of underspecified queries trigger a follow-up quest...

Rong-Yu Zhang, Mu-Tian Bao, Jin-Jian Zhang et al. · Proceedings of the 2026 Conf... · 0 citations

Aug 2026

CARE: Confidence-Aware Reasoning for Reliable Medical VQA

Reinforcement Fine-Tuning (RFT) has enabled medical Multimodal Large Language Models (MLLMs) to produce Chain-of-Thought (CoT) reasoning for visual question answering, yet these models suffer from $\textit{confidence miscalibration}$---a systematic gap between expressed certainty and actual diagnostic accuracy that und...

Yuetian Du, Yu-Cheng Wang, Zhenyuan Chen et al. · Lecture notes in computer sc... · 0 citations

#artificial intelligence Preprint Aug 2026

The Illusion of $\textit{What If}$: Evaluating the Breakdown of Counterfactual Reasoning in LLMs

A diagnostic benchmark for open-domain, open-form, long-horizon counterfactual causal reasoning, containing 220 what-if questions across STEM, HSS, and Hybrid scenarios, and finds that WhatIfBench remains far from saturated: even the strongest model reaches only a 64.62% final score.

Yu-Cheng Wang, Yuetian Du, Zheng Liu et al. · 0 citations