7 citations · 16 across the 21 of their papers we have counts for
7 papers · 1 filter
Federation over Harness
Dixi Yao, Tahseen Rabbani, Tian Li
Modern LLM-powered agents increasingly improve through experience sharing, where distributed agents distill local reasoning experience into reusable knowledge, such as a shared ins…
Private Retrieval Augmented Generation via Random Projection
Dixi Yao, Tahseen Rabbani, Tian Li
Retrieval-Augmented Generation (RAG) enhances the capabilities of large language models (LLMs) by querying external structured knowledge. However, it can also introduce privacy ris…
SEIS: Self-Evolving Inference Systems
Zhen Xu, Jingyu Liu, Zongze Li +2
Inference systems determine how fast and how cheaply language models can be served, so making them faster has direct practical value. However, prior work focuses mostly on optimizi…
Persistent Watermarking of Text-to-Image Models
Dixi Yao, Kaiwen Chen, Tahseen Rabbani +1
Text-to-image (T2I) generation is gaining increasing popularity with the general public, motivating the development of reliable mechanisms for copyrighting such models given their…
Federation over Text: Insight Sharing for Multi-Agent Reasoning
Dixi Yao, Tahseen Rabbani, Manzil Zaheer +1
Modern agents specialize in varying domains while there is no clear approach combining different domain skills. We propose a federated learning-like framework, Federation over Text…
Not All Prefills Are Equal: PPD Disaggregation for Multi-turn LLM Serving
Zongze Li, Jingyu Liu, Zhen Xu +3
Prefill-Decode (PD) disaggregation has become the standard architecture for modern LLM inference engines, which alleviates the interference of two distinctive workloads. With the g…
Asynchronous Heavy-Tailed Optimization
Junfei Sun, Dixi Yao, Xuchen Gong +3
Heavy-tailed stochastic gradient noise, commonly observed in transformer models, can destabilize the optimization process. Recent works mainly focus on developing and understanding…