3 papers
cs.CL2026
Memory vs. Context? Influential Factors of Factual Recall in Language Models
Guilhem Fouilhé, Nicholas Asher, Philippe Muller
We reproduce and stress-test the work of Yu et al. (2023), who characterize how language models (LMs) arbitrate between memorized knowledge and contradictory in-context statements.…
cs.AI2026
Exploring Plan Space through Conversation: An Agentic Framework for LLM-Mediated Explanations in Planning
Guilhem Fouilhé, Rebecca Eifler, Antonin Poché +2
When automating plan generation for a real-world sequential decision problem, the goal is often not to replace the human planner, but to facilitate an iterative reasoning and elici…
cs.LG2024
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…