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The George Washington University, Northeastern University
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Persistent homology reveals a structured approach to understanding and steering LLM responses to ambiguous questions, boosting accuracy and acceptable response rates significantly.
LLMs and VLMs excel at conceptual tasks but falter in practical execution, achieving only 42.2% success in script generation for VLSI design.
By distilling successful and failed reasoning paths into a "Cognitive Tree," T-STAR pinpoints and corrects critical errors in multi-turn reasoning, leading to significant performance gains.
