1 citations · 1 across the 5 of their papers we have counts for
13 papers
Joint Continual Learning of Local Language Models and Cloud Offloading Decisions with Budget Constraints
Evan Chen, Wenzhi Fang, Shiqiang Wang +1
Locally deployed Small Language Models (SLMs) must continually support diverse tasks under strict memory and computation constraints, making selective reliance on cloud Large Langu…
Sporadic Gradient Tracking over Directed Graphs: A Theoretical Perspective on Decentralized Federated Learning
Shahryar Zehtabi, Dong-Jun Han, Seyyedali Hosseinalipour +1
Decentralized Federated Learning (DFL) enables clients with local data to collaborate in a peer-to-peer manner to train a generalized model. In this paper, we unify two branches of…
Adversarial Node Placement in Decentralized Federated Learning: Maximum Spanning-Centrality Strategy and Performance Analysis
Adam Piaseczny, Eric Ruzomberka, Rohit Parasnis +1
As Federated Learning (FL) becomes more widespread, there is growing interest in its decentralized variants. Decentralized FL leverages the benefits of fast and energy-efficient de…
Next-Generation LLM for UAV: From Natural Language to Autonomous Flight
Liangqi Yuan, Chuhao Deng, Dong-Jun Han +3
With the rapid advancement of Large Language Models (LLMs), their capabilities in various automation domains, particularly Unmanned Aerial Vehicle (UAV) operations, have garnered i…
LLMAP: LLM-Assisted Multi-Objective Route Planning with User Preferences
Liangqi Yuan, Dong-Jun Han, Christopher G. Brinton +1
The rise of large language models (LLMs) has made natural language-driven route planning an emerging research area that encompasses rich user objectives. Current research exhibits…
Contextual Integrity in LLMs via Reasoning and Reinforcement Learning
Guangchen Lan, Huseyin A. Inan, Sahar Abdelnabi +5
As the era of autonomous agents making decisions on behalf of users unfolds, ensuring contextual integrity (CI) -- what is the appropriate information to share while carrying out a…