Look Back to Reason Forward: Revisitable Memory for Long-Context LLM Agents

Researchers introduce ReMemR1, a new approach to improve large language models' ability to handle long-context question answering by integrating memory retrieval into the memory update process. The system enables non-linear reasoning through selective callback of historical memories and uses multi-level reward design to strengthen training.