4 papers
COCORELI: Enforcing Execution Preconditions for Reliable Collaborative Instruction Following
Swarnadeep Bhar, Omar Naim, Eleni Metheniti +4
Autonomous agents executing human instructions must operate reliably even when instructions are incomplete. While recent approaches improve detection of missing information, detect…
Analyzing limits for in-context learning
Omar Naim, Jerome Bolte, Nicholas Asher
Our paper challenges claims from prior research that transformer-based models, when learning in context, implicitly implement standard learning algorithms. We present empirical evi…
Re-examining learning linear functions in context
Omar Naim, Guilhem Fouilhé, Nicholas Asher
In-context learning (ICL) has emerged as a powerful paradigm for easily adapting Large Language Models (LLMs) to various tasks. However, our understanding of how ICL works remains…
On Explaining with Attention Matrices
Omar Naim, Nicholas Asher
This paper explores the much discussed, possible explanatory link between attention weights (AW) in transformer models and predicted output. Contrary to intuition and early researc…