10 papers
Latent Visual Cache for Video Reasoning
Yongheng Zhang, Zhipeng Xu, Hao Wu +4
Video reasoning requires Large Multimodal Models (LMMs) to remain grounded in dense evidence, yet existing systems largely adopt "read-once, generate-many" paradigm, in which visua…
From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI
Yongheng Zhang, Ziang Liu, Jiaxuan Zhu +17
Large Language Models (LLMs) are undergoing a fundamental transformation from conversational generators into integrated AI systems capable of reasoning, action, memory, and self-im…
Cognitive Mismatch in Multimodal Large Language Models for Discrete Symbol Understanding
Yinghui Li, Jiayi Kuang, Peng Xing +11
Multimodal large language models (MLLMs) perform strongly on natural images, yet their ability to understand discrete visual symbols remains unclear. We present a multi-domain benc…
RAISE: Reinforced Adaptive Instruction Selection For Large Language Models
Qingsong Lv, Yangning Li, Zihua Lan +8
In the instruction fine-tuning of large language models (LLMs), it is widely recognized that a few high-quality instructions are superior to a large number of low-quality instructi…
TangramPuzzle: Evaluating Multimodal Large Language Models with Compositional Spatial Reasoning
Daixian Liu, Jiayi Kuang, Yinghui Li +8
Multimodal Large Language Models (MLLMs) have achieved remarkable progress in visual recognition and semantic understanding. Nevertheless, their ability to perform precise composit…
Large Language Models Meet NLP: A Survey
Libo Qin, Qiguang Chen, Xiachong Feng +6
While large language models (LLMs) like ChatGPT have shown impressive capabilities in Natural Language Processing (NLP) tasks, a systematic investigation of their potential in this…