9 citations · 14 across the 4 of their papers we have counts for
Showing 2023Show all
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cs.CL2023★ 4 cited
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent
Renat Aksitov, Sobhan Miryoosefi, Zonglin Li +10
Answering complex natural language questions often necessitates multi-step reasoning and integrating external information. Several systems have combined knowledge retrieval with a…
cs.LG2023★ 9 cited
Collaborating with language models for embodied reasoning
Ishita Dasgupta, Christine Kaeser-Chen, Kenneth Marino +4
Reasoning in a complex and ambiguous environment is a key goal for Reinforcement Learning (RL) agents. While some sophisticated RL agents can successfully solve difficult tasks, th…