Modern language agents need to handle multi-turn conversations, retrieving and updating information as tasks evolve. However, most current systems simply add all past interactions to the prompt, regardless of relevance. This leads…
MIT and NUS Researchers Introduce MEM1: A Memory-Efficient Framework for Long-Horizon Language Agents
