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Papers Explained 371: ReasonIRReasonIR-8B is a novel bi-encoder retriever specifically designed for reasoning-intensive retrieval tasks. It addresses the limitations of…2h ago2h ago
Papers Explained 370: Test Time Reinforcement Learning (TTRL)Test-Time Reinforcement Learning (TTRL) is a method for training LLMs using RL on unlabeled data. TTRL enables self-evolution of LLMs by…1d ago1d ago
Papers Explained 369: RM-R1RM-R1 is a family of Reasoning Reward Models designed to improve the interpretability and performance of large language models (LLMs) by…2d ago2d ago
Papers Explained 368: ThinkPRMThinkPRM, a long CoT verifier fine-tuned on orders of magnitude fewer process labels than those required by discriminative PRMs. This…3d ago3d ago
Papers Explained 366: Math ShepherdMath Shepherd is a process-oriented math process reward model that assigns a reward score to each step of a math problem solution, enabling…May 15A response icon1May 15A response icon1
Papers Explained 365: DeepMathDeepMath-103K is a new dataset designed for advancing mathematical reasoning research. It comprises 103,000 mathematical problems with a…May 14May 14
Papers Explained 364: OmniMathOmniMath is a comprehensive and challenging benchmark specifically designed to assess LLMs’ mathematical reasoning at the Olympiad level…May 13May 13
