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cs.CL2025
Cross-Examiner: Evaluating Consistency of Large Language Model-Generated Explanations
Danielle Villa, Maria Chang, Keerthiram Murugesan +2
Large Language Models (LLMs) are often asked to explain their outputs to enhance accuracy and transparency. However, evidence suggests that these explanations can misrepresent the…
cs.CL2024
Reasoning about concepts with LLMs: Inconsistencies abound
Rosario Uceda-Sosa, Karthikeyan Natesan Ramamurthy, Maria Chang +1
The ability to summarize and organize knowledge into abstract concepts is key to learning and reasoning. Many industrial applications rely on the consistent and systematic use of c…
cs.CL2024
Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations
Swapnaja Achintalwar, Ioana Baldini, Djallel Bouneffouf +16
The alignment of large language models is usually done by model providers to add or control behaviors that are common or universally understood across use cases and contexts. In co…