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Srinagesh Sharma

2 accepted papers

2025

RLTHF: Targeted Human Feedback for LLM Alignment

ICML 2025poster

Fine-tuning large language models (LLMs) to align with user preferences is challenging due to the high cost of quality human annotations in Reinforcement Learning from Human Feedback (RLHF) and the generalizability limitations of AI Feedback. To address these challenges, we propose RLTHF, a human-AI…

Cited by 0SourcePDFScholar
2025

Steering Large Language Models between Code Execution and Textual Reasoning

ICLR 2025poster

While a lot of recent research focuses on enhancing the textual reasoning capabilities of Large Language Models (LLMs) by optimizing the multi-agent framework or reasoning chains, several benchmark tasks can be solved with 100\% success through direct coding, which is more scalable and avoids the co…