2 papers
cs.CL2026
Learning to Learn from Language Feedback with Social Meta-Learning
Jonathan Cook, Diego Antognini, Martin Klissarov +2
Large language models (LLMs) often struggle to learn from corrective feedback within a conversational context. They are rarely proactive in soliciting this feedback, even when face…
cs.AI2026
Improving Interactive In-Context Learning from Natural Language Feedback
Martin Klissarov, Jonathan Cook, Diego Antognini +5
Adapting one's thought process based on corrective feedback is an essential ability in human learning, particularly in collaborative settings. In contrast, the current large langua…