3 papers
cs.CL2025
OmniStruct: Universal Text-to-Structure Generation across Diverse Schemas
James Y. Huang, Wenxuan Zhou, Nan Xu +5
The ability of Large Language Models (LLMs) to generate structured outputs that follow arbitrary schemas is crucial to a wide range of downstream tasks that require diverse structu…
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…