68 citations · 105 across the 4 of their papers we have counts for
4 papers
When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o1
R. Thomas McCoy, Shunyu Yao, Dan Friedman +2
In "Embers of Autoregression" (McCoy et al., 2023), we showed that several large language models (LLMs) have some important limitations that are attributable to their origins in ne…
Are LLMs Good Cryptic Crossword Solvers?
Abdelrahman Sadallah, Daria Kotova, Ekaterina Kochmar
Cryptic crosswords are puzzles that rely not only on general knowledge but also on the solver's ability to manipulate language on different levels and deal with various types of wo…
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…