2 papers
cs.AI2026
Cognitive Demand Steering for Adaptive Meta-Reasoning in Large Language Models
John Scoville, Shengzhuang Chen, Yejin Bang +2
Recent meta-reasoning frameworks improve LLM reasoning by wrapping chain-of-thought generation in an iterative control loop, allowing more effective backtracking, termination of re…
cs.LG2026
CapTrack: Multifaceted Evaluation of Forgetting in LLM Post-Training
Lukas Thede, Stefan Winzeck, Zeynep Akata +1
Large language model (LLM) post-training enhances latent skills, unlocks value alignment, improves performance, and enables domain adaptation. Unfortunately, post-training is known…