2 papers
cs.LG2026
REVES: REvision and VErification--Augmented Training for Test-Time Scaling
Yuanxin Liu, Ruida Zhou, Xinyan Zhao +6
Test-time scaling via sequential revision has emerged as a powerful paradigm for enhancing Large Language Model (LLM) reasoning. However, standard post-training methods primarily o…
cs.CL2026
Modeling Multi-Dimensional Cognitive States in Large Language Models under Cognitive Crowding
Lin Zhong, Siyu Zhu, Zizhen Yuan +5
Modeling human cognitive states is essential for advanced artificial intelligence. Existing Large Language Models (LLMs) mainly address isolated tasks such as emotion analysis or s…