5 papers
DynamicGTR: Leveraging Graph Topology Representation Preferences to Boost VLM Capabilities on Graph QAs
Yanbin Wei, Jiangyue Yan, Chun Kang +4
Vision-Language Models (VLMs) have emerged as versatile solutions for zero-shot question answering (QA) across various domains. However, enabling VLMs to effectively comprehend str…
Harnessing Adaptive Topology Representations for Zero-Shot Graph Question Answering
Yanbin Wei, Jiangyue Yan, Chun Kang +4
Large Multimodal Models (LMMs) have shown generalized zero-shot capabilities in diverse domain question-answering (QA) tasks, including graph QA that involves complex graph topolog…
A Survey on Post-training of Large Language Models
Guiyao Tie, Zeli Zhao, Dingjie Song +23
The emergence of Large Language Models (LLMs) has fundamentally transformed natural language processing, making them indispensable across domains ranging from conversational system…
Agentic Robot: A Brain-Inspired Framework for Vision-Language-Action Models in Embodied Agents
Zhejian Yang, Yongchao Chen, Xueyang Zhou +8
Long-horizon robotic manipulation poses significant challenges for autonomous systems, requiring extended reasoning, precise execution, and robust error recovery across complex seq…
DynamicMind: A Tri-Mode Thinking System for Large Language Models
Wei Li, Yanbin Wei, Qiushi Huang +4
Modern large language models (LLMs) often struggle to dynamically adapt their reasoning depth to varying task complexities, leading to suboptimal performance or inefficient resourc…