1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Mixture of Complementary Agents for Robust LLM Ensemble
Yichi Zhang, Kevin Lu, Yuang Zhang +3
Multi-AI collaboration, such as ensembling or debating large language models (LLMs), is a promising paradigm for aggregating information and boosting performance. A foundational st…
cs.AI2026
Agent-as-Peer-Debriefer: A Multi-Agent Framework with Perspective-Based Refinement for Qualitative Analysis
Zhimin Lin, Kun Cheng, Zhiyao Shu +4
Large language models (LLMs) are increasingly used for qualitative data analysis (QDA), yet their outputs often miss the depth and nuance of human analysis. We argue this gap refle…
cs.HC2023★ 1 cited
Impact of Human-AI Interaction on User Trust and Reliance in AI-Assisted Qualitative Coding
Jie Gao, Junming Cao, ShunYi Yeo +5
While AI shows promise for enhancing the efficiency of qualitative analysis, the unique human-AI interaction resulting from varied coding strategies makes it challenging to develop…