3 papers
cs.AI2025
MetaVLA: Unified Meta Co-training For Efficient Embodied Adaption
Chen Li, Zhantao Yang, Han Zhang +4
Vision-Language-Action (VLA) models show promise in embodied reasoning, yet remain far from true generalists-they often require task-specific fine-tuning, incur high compute costs,…
cs.AI2025
STELAR-VISION: Self-Topology-Aware Efficient Learning for Aligned Reasoning in Vision
Chen Li, Han Zhang, Zhantao Yang +4
Vision-language models (VLMs) have made significant strides in reasoning, yet they often struggle with complex multimodal tasks and tend to generate overly verbose outputs. A key l…
cs.AI2025
SOLAR: Scalable Optimization of Large-scale Architecture for Reasoning
Chen Li, Yinyi Luo, Anudeep Bolimera +4
Large Language Models excel in reasoning yet often rely on Chain-of-Thought prompts, limiting performance on tasks demanding more nuanced topological structures. We present SOLAR (…