SignalReasoner: Assessing the Upper Bound of 3B Models for Signal Mathematical Reasoning: Post-training with supervised...
Chain-of-thought fine-tuning and reinforcement learning from verifiable rewards has substantially improved the mathematical reasoning capabilities of large language models (LLMs). However, their application to signal processing problems remains relatively under-explored. This report investigates reinforcement fine-tuning stra...
来源简报
SignalReasoner: Assessing the Upper Bound of 3B Models for Signal Mathematical Reasoning: Post-training with supervised chain-of-thought fine-tuning and reinforcement learning from verifiable rewards has substantially improved the mathematical reasoning capabilities of large language models (LLMs). However, their application to signal processing problems remains relatively under-explored. This report investigates reinforcement fine-tuning stra...