29 citations · 55 across the 27 of their papers we have counts for
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Cross-Refine: Improving Natural Language Explanation Generation by Learning in Tandem
Qianli Wang, Tatiana Anikina, Nils Feldhus +3
Natural language explanations (NLEs) are vital for elucidating the reasoning behind large language model (LLM) decisions. Many techniques have been developed to generate NLEs using…
Free-text Rationale Generation under Readability Level Control
Yi-Sheng Hsu, Nils Feldhus, Sherzod Hakimov
Free-text rationales justify model decisions in natural language and thus become likable and accessible among approaches to explanation across many tasks. However, their effectiven…
CoXQL: A Dataset for Parsing Explanation Requests in Conversational XAI Systems
Qianli Wang, Tatiana Anikina, Nils Feldhus +2
Conversational explainable artificial intelligence (ConvXAI) systems based on large language models (LLMs) have garnered significant interest from the research community in natural…
LLMCheckup: Conversational Examination of Large Language Models via Interpretability Tools and Self-Explanations
Qianli Wang, Tatiana Anikina, Nils Feldhus +3
Interpretability tools that offer explanations in the form of a dialogue have demonstrated their efficacy in enhancing users' understanding (Slack et al., 2023; Shen et al., 2023),…