1 citations · 3 across the 5 of their papers we have counts for
7 papers
Dep-Search: Learning Dependency-Aware Reasoning Traces with Persistent Memory
Yanming Liu, Xinyue Peng, Zixuan Yan +7
Large Language Models (LLMs) have demonstrated remarkable capabilities in complex reasoning tasks, particularly when augmented with search mechanisms that enable systematic explora…
Digital Twin AI: Opportunities and Challenges from Large Language Models to World Models
Rong Zhou, Dongping Chen, Zihan Jia +24
Digital twins, as precise digital representations of physical systems, have evolved from passive simulation tools into intelligent and autonomous entities through the integration o…
TASE: Token Awareness and Structured Evaluation for Multilingual Language Models
Chenzhuo Zhao, Xinda Wang, Yue Huang +2
While large language models (LLMs) have demonstrated remarkable performance on high-level semantic tasks, they often struggle with fine-grained, token-level understanding and struc…
EfficientLLM: Efficiency in Large Language Models
Zhengqing Yuan, Weixiang Sun, Yixin Liu +13
Large Language Models (LLMs) have driven significant progress, yet their growing parameter counts and context windows incur prohibitive compute, energy, and monetary costs. We intr…
Generative AI for Autonomous Driving: Frontiers and Opportunities
Yuping Wang, Shuo Xing, Cui Can +44
Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled capabilities for content creation,…
ReadMe.LLM: A Framework to Help LLMs Understand Your Library
Sandya Wijaya, Jacob Bolano, Alejandro Gomez Soteres +3
Large Language Models (LLMs) often struggle with code generation tasks involving niche software libraries. Existing code generation techniques with only human-oriented documentatio…