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cs.CL2025
MetaScale: Test-Time Scaling with Evolving Meta-Thoughts
Qin Liu, Wenxuan Zhou, Nan Xu +5
One critical challenge for large language models (LLMs) for making complex reasoning is their reliance on matching reasoning patterns from training data, instead of proactively sel…
cs.CV2025
Semantic-Clipping: Efficient Vision-Language Modeling with Semantic-Guidedd Visual Selection
Bangzheng Li, Fei Wang, Wenxuan Zhou +5
Vision-Language Models (VLMs) leverage aligned visual encoders to transform images into visual tokens, allowing them to be processed similarly to text by the backbone large languag…
cs.CL2025★ 2 cited
Med-RLVR: Emerging Medical Reasoning from a 3B base model via reinforcement Learning
Sheng Zhang, Qianchu Liu, Guanghui Qin +2
Reinforcement learning from verifiable rewards (RLVR) has recently gained attention for its ability to elicit self-evolved reasoning capabilitie from base language models without e…