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cs.AI2026
UniEvo-VL: An On-policy Self-Distillation Training Recipe for Multimodal Model Self-improvement
Fang Wu, Da Xing, Yanjie Huang +16
Modern multimodal models bring generation and understanding into a single unified system, which enables them to provide and learn from their own feedback. Motivated by this unified…
cs.AI2026
Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations
Bowen Zuo, Dongruo Zhou, Yinglun Zhu
While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from fixed generation distributi…
cs.AI2025
Strategic Scaling of Test-Time Compute: A Bandit Learning Approach
Bowen Zuo, Yinglun Zhu
Scaling test-time compute has emerged as an effective strategy for improving the performance of large language models. However, existing methods typically allocate compute uniforml…