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Niruthikka Sritharan on Muck Rack

Niruthikka Sritharan

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Articles

When the Chain Breaks: Interactive Diagnosis of LLM Chain-of-Thought Reasoning Errors

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By Shiwei Chen, Nanyang Technological Singapore, Niruthikka Sritharan
| Wiley Online Library Verified
1. Introduction In the past few years, large language models (LLMs) have become foundational across diverse real-world tasks, such as information seeking, decision-making, and practical guidance [CCD*25]. Chain-of-Thought (CoT) prompting [WWS*22] improves task performance by encouraging models to output intermediate reasoning steps in natural language, producing a human-readable reasoning trace.
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