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Yining Hua

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Preprint Aug 2026

LLMs for Medical Consultation Are Evaluated Too Late: The Preformulation Gap

Large language models for medical consultation are often evaluated after a clinical problem has already been made clear, although real consultations may begin with a vague, minimized, or misframed concern. We evaluated three API models across four physician-authored, multi-turn vignettes under baseline and entry-to-car...

Yining Hua, C. Ayubcha, Hongbin Na et al. · 0 citations
#artificial intelligence Preprint Sep 2026

WorkWorlds: An Infrastructure for Evaluating AI Agents on Workplace Tasks

This work introduces WorkWorlds, an evaluation infrastructure that separates organizational state from task specification, and implements WorkWorlds in a primary synthetic pharmaceutical company with 8 measured tasks across 6 employee seats, and construct additional organizational worlds.

Yining Hua, Levi Lian · 0 citations
Preprint Aug 2026

CARE-Bench: Benchmarking Patient-Facing LLM Triage

CARE-Bench, a source-grounded benchmark that evaluates sequential patient-facing triage as a four-label per-turn current-action task, is introduced, which improves 10 of 11 models and supports explicit evaluation of action timing before deployment.

Yining Hua, Hongbin Na, C. Ayubcha · 0 citations
#natural language process... Conference Dec 2024

Detecting Conversational Mental Manipulation with Intent-Aware Prompting

Intent-Aware Prompting (IAP) is proposed, a novel approach for detecting mental manipulations using large language models (LLMs), providing a deeper understanding of manipulative tactics by capturing the underlying intents of participants.

Jiayuan Ma, Hongbin Na, Zimu Wang et al. · 24 citations · ⚡3
Review Aug 2026

StagedWorkspace: A Versioned Workspace for Knowledge-Work Agents

StagedWorkspace is proposed, a versioned workspace for knowledge-work agents that binds parsed records and review diffs to content hashes of the native files as they change, and motivates benchmarks that score evidence, staged edits, and submitted artifacts as explicit state transitions.

Yining Hua, Hongbin Na, Yifan Zhou et al. · 0 citations

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