most citedRT-LM: Uncertainty-Aware Resource Management for Real-Time Inference of Language Models

1 citations · 2 across the 3 of their papers we have counts for

collaborators

6 papers

cs.LG2025

MACE: A Hybrid LLM Serving System with Colocated SLO-aware Continuous Retraining Alignment

Yufei Li, Yu Fu, Yue Dong +1

Large language models (LLMs) deployed on edge servers are increasingly used in latency-sensitive applications such as personalized assistants, recommendation, and content moderatio…

cs.CL2025

Dr Genre: Reinforcement Learning from Decoupled LLM Feedback for Generic Text Rewriting

Yufei Li, John Nham, Ganesh Jawahar +7

Generic text rewriting is a prevalent large language model (LLM) application that covers diverse real-world tasks, such as style transfer, fact correction, and email editing. These…

cs.CL2023

Safety Alignment in NLP Tasks: Weakly Aligned Summarization as an In-Context Attack

Yu Fu, Yufei Li, Wen Xiao +2

Recent developments in balancing the usefulness and safety of Large Language Models (LLMs) have raised a critical question: Are mainstream NLP tasks adequately aligned with safety…

cs.CL2023

Distantly-Supervised Joint Extraction with Noise-Robust Learning

Yufei Li, Xiao Yu, Yanghong Guo +3

Joint entity and relation extraction is a process that identifies entity pairs and their relations using a single model. We focus on the problem of joint extraction in distantly-la…

cs.LG20231 cited

RT-LM: Uncertainty-Aware Resource Management for Real-Time Inference of Language Models

Yufei Li, Zexin Li, Wei Yang +1

Recent advancements in language models (LMs) have gained substantial attentions on their capability to generate human-like responses. Though exhibiting a promising future for vario…

cs.LG20231 cited

GLAD: Content-aware Dynamic Graphs For Log Anomaly Detection

Yufei Li, Yanchi Liu, Haoyu Wang +6

Logs play a crucial role in system monitoring and debugging by recording valuable system information, including events and states. Although various methods have been proposed to de…