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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…
cs.AI2026
Position: Introspective Experience from Conversational Environments as a Path to Better Learning
Claudiu Cristian Musat, Jackson Tolins, Diego Antognini +3
Current approaches to AI training treat reasoning as an emergent property of scale. We argue instead that robust reasoning emerges from linguistic self-reflection, itself internali…