6 citations · 6 across the 6 of their papers we have counts for
3 papers · 1 filter
Teaching People LLM's Errors and Getting it Right
Nathan Stringham, Fateme Hashemi Chaleshtori, Xinyuan Yan +3
People use large language models (LLMs) when they should not. This is partly because they see LLMs compose poems and answer intricate questions, so they understandably, but incorre…
Explainable Mapper: Charting LLM Embedding Spaces Using Perturbation-Based Explanation and Verification Agents
Xinyuan Yan, Rita Sevastjanova, Sinie van der Ben +2
Large language models (LLMs) produce high-dimensional embeddings that capture rich semantic and syntactic relationships between words, sentences, and concepts. Investigating the to…
VISLIX: An XAI Framework for Validating Vision Models with Slice Discovery and Analysis
Xinyuan Yan, Xiwei Xuan, Jorge Piazentin Ono +6
Real-world machine learning models require rigorous evaluation before deployment, especially in safety-critical domains like autonomous driving and surveillance. The evaluation of…