6 papers · 1 filter
Indications of Belief-Guided Agency and Meta-Cognitive Monitoring in Large Language Models
Noam Steinmetz Yalon, Ariel Goldstein, Liad Mudrik +1
Rapid advancements in large language models (LLMs) have sparked the question whether these models possess some form of consciousness. To tackle this challenge, Butlin et al. (2023)…
SAUCE: Synchronous and Asynchronous User-Customizable Environment for Multi-Agent LLM Interaction
Shlomo Neuberger, Niv Eckhaus, Uri Berger +3
Many human interactions, such as political debates, are carried out in group settings, where there are arbitrarily many participants, each with different views and agendas. To expl…
Looking Beyond The Top-1: Transformers Determine Top Tokens In Order
Daria Lioubashevski, Tomer Schlank, Gabriel Stanovsky +1
Understanding the inner workings of Transformers is crucial for achieving more accurate and efficient predictions. In this work, we analyze the computation performed by Transformer…
Distributional reasoning in LLMs: Parallel reasoning processes in multi-hop reasoning
Yuval Shalev, Amir Feder, Ariel Goldstein
Large language models (LLMs) have shown an impressive ability to perform tasks believed to require thought processes. When the model does not document an explicit thought process,…
A Nurse is Blue and Elephant is Rugby: Cross Domain Alignment in Large Language Models Reveal Human-like Patterns
Asaf Yehudai, Taelin Karidi, Gabriel Stanovsky +2
Cross-domain alignment refers to the task of mapping a concept from one domain to another. For example, ``If a \textit{doctor} were a \textit{color}, what color would it be?''. Thi…
Do Zombies Understand? A Choose-Your-Own-Adventure Exploration of Machine Cognition
Ariel Goldstein, Gabriel Stanovsky
Recent advances in LLMs have sparked a debate on whether they understand text. In this position paper, we argue that opponents in this debate hold different definitions for underst…