288 citations · 504 across the 15 of their papers we have counts for
5 papers · 1 filter
Embers of Autoregression: Understanding Large Language Models Through the Problem They are Trained to Solve
R. Thomas McCoy, Shunyu Yao, Dan Friedman +2
The widespread adoption of large language models (LLMs) makes it important to recognize their strengths and limitations. We argue that in order to develop a holistic understanding…
Cognitive Architectures for Language Agents
Theodore R. Sumers, Shunyu Yao, Karthik Narasimhan +1
Recent efforts have augmented large language models (LLMs) with external resources (e.g., the Internet) or internal control flows (e.g., prompt chaining) for tasks requiring ground…
Personality Understanding of Fictional Characters during Book Reading
Mo Yu, Jiangnan Li, Shunyu Yao +5
Comprehending characters' personalities is a crucial aspect of story reading. As readers engage with a story, their understanding of a character evolves based on new events and inf…
EC^2: Emergent Communication for Embodied Control
Yao Mu, Shunyu Yao, Mingyu Ding +2
Embodied control requires agents to leverage multi-modal pre-training to quickly learn how to act in new environments, where video demonstrations contain visual and motion details…
Reflexion: Language Agents with Verbal Reinforcement Learning
Noah Shinn, Federico Cassano, Edward Berman +3
Large language models (LLMs) have been increasingly used to interact with external environments (e.g., games, compilers, APIs) as goal-driven agents. However, it remains challengin…