5 citations · 13 across the 12 of their papers we have counts for
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cs.CL2025
Learning from Supervision with Semantic and Episodic Memory: A Reflective Approach to Agent Adaptation
Jackson Hassell, Dan Zhang, Hannah Kim +2
We investigate how agents built on pretrained large language models (LLMs) can learn target classification functions from labeled examples without parameter updates. While conventi…
cs.HC2025
AIPOM: Agent-aware Interactive Planning for Multi-Agent Systems
Hannah Kim, Kushan Mitra, Chen Shen +2
Large language models (LLMs) are being increasingly used for planning in orchestrated multi-agent systems. However, existing LLM-based approaches often fall short of human expectat…
cs.CL2025
RECAP: REwriting Conversations for Intent Understanding in Agentic Planning
Kushan Mitra, Dan Zhang, Hannah Kim +1
Understanding user intent is essential for effective planning in conversational assistants, particularly those powered by large language models (LLMs) coordinating multiple agents.…