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cs.AI2026
Teaching LLMs String Matching, Backtracking, and Error Recovery to Deduce Bases and Truth Tables for the Combinatorially Exploding Bit Manipulation Puzzles
Prateek Agnihotri, Sanchit Jain, Prabhat Agnihotri +2
This paper presents our algorithmic innovations for the NVIDIA Nemotron Model Reasoning Challenge, focusing on Bit Manipulation Puzzles. In this task, the objective is to discover…
cs.AI2026
RLHFless: Serverless Computing for Efficient RLHF
Rui Wei, Hanfei Yu, Shubham Jain +5
Reinforcement Learning from Human Feedback (RLHF) has been widely applied to Large Language Model (LLM) post-training to align model outputs with human preferences. Recent models,…