31 citations · 31 across the 5 of their papers we have counts for
5 papers
BudgetThinker: Empowering Budget-aware LLM Reasoning with Control Tokens
Hao Wen, Xinrui Wu, Yi Sun +7
Recent advancements in Large Language Models (LLMs) have leveraged increased test-time computation to enhance reasoning capabilities, a strategy that, while effective, incurs signi…
An Empirical Study of LLM Reasoning Ability Under Strict Output Length Constraint
Yi Sun, Han Wang, Jiaqiang Li +8
Recent work has demonstrated the remarkable potential of Large Language Models (LLMs) in test-time scaling. By making models think before answering, they are able to achieve much h…
ChainStream: An LLM-based Framework for Unified Synthetic Sensing
Jiacheng Liu, Yuanchun Li, Liangyan Li +5
Many applications demand context sensing to offer personalized and timely services. Yet, developing sensing programs can be challenging for developers and using them is privacy-con…
Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
Yuanchun Li, Hao Wen, Weijun Wang +22
Since the advent of personal computing devices, intelligent personal assistants (IPAs) have been one of the key technologies that researchers and engineers have focused on, aiming…
Generative Model for Models: Rapid DNN Customization for Diverse Tasks and Resource Constraints
Wenxing Xu, Yuanchun Li, Jiacheng Liu +5
Unlike cloud-based deep learning models that are often large and uniform, edge-deployed models usually demand customization for domain-specific tasks and resource-limited environme…