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cs.CV2026
Weak-to-Strong Knowledge Distillation Accelerates Visual Learning
Baiang Li, Wenhao Chai, Felix Heide
Large-scale visual learning is increasingly limited by training cost. Existing knowledge distillation methods transfer from a stronger teacher to a weaker student for compression o…
cs.CV2025
Hybrid Token Compression for Vision-Language Models
Jusheng Zhang, Xiaoyang Guo, Tongyu Mo +5
Vision-language models (VLMs) rely on hundreds of visual tokens, leading to high computational and memory costs. Existing compression methods face a trade-off: continuous compressi…
cs.CV2025
MM-HELIX: Boosting Multimodal Long-Chain Reflective Reasoning with Holistic Platform and Adaptive Hybrid Policy Optimization
Xiangyu Zhao, Junming Lin, Tianhao Liang +11
While current Multimodal Large Language Models (MLLMs) have demonstrated proficiency in reasoning tasks such as mathematics and logic, their capacity for long-chain reflective reas…