G2: A Network Optimization Framework for High-Precision Analysis of Bottleneck and Flow Performance. - Jordi Ros-Giralt; Leandros Tassiulas; Sruthi Yellamraju; Atul Bohara; Richard Lethin; Josie Li; Ying Lin; Yuanlong Tan; Malathi Veeraraghavan; Yuang Jiang (INDIS@SC, 2019)

Model Pruning Enables Efficient Federated Learning on Edge Devices. - Yuang Jiang; Shiqiang Wang 001; Bong Jun Ko; Wei-Han Lee; Leandros Tassiulas (CoRR, 2019)

On the Bottleneck Structure of Congestion-Controlled Networks. - Jordi Ros-Giralt; Atul Bohara; Sruthi Yellamraju; Matthew Harper Langston; Richard Lethin; Yuang Jiang; Leandros Tassiulas; Josie Li; Yuanlong Tan; Malathi Veeraraghavan (Proc. ACM Meas. Anal. Comput. Syst., 2019)

Fast Reinforcement Learning Algorithms for Resource Allocation in Data Centers. - Yuang Jiang; Murali S. Kodialam; T. V. Lakshman; Sarit Mukherjee; Leandros Tassiulas (Networking, 2020)

Designing data center networks using bottleneck structures. - Jordi Ros-Giralt; Noah Amsel; Sruthi Yellamraju; James R. Ezick; Richard Lethin; Yuang Jiang; Aosong Feng; Leandros Tassiulas; Zhenguo Wu; Min Yee Teh; Keren Bergman (SIGCOMM, 2021)

Resource Allocation in Data Centers Using Fast Reinforcement Learning Algorithms. - Yuang Jiang; Murali S. Kodialam; T. V. Lakshman; Sarit Mukherjee; Leandros Tassiulas (IEEE Trans. Netw. Serv. Manag., 2021)

Robust and Resource-efficient Machine Learning Aided Viewport Prediction in Virtual Reality. - Yuang Jiang; Konstantinos Poularakis; Diego Kiedanski; Sastry Kompella; Leandros Tassiulas (IEEE Big Data, 2022)

A Quantitative Theory of Bottleneck Structures for Data Networks. - Jordi Ros-Giralt; Noah Amsel; Sruthi Yellamraju; James R. Ezick; Richard Lethin; Yuang Jiang; Aosong Feng; Leandros Tassiulas (CoRR, 2022)

Diffuser: Efficient Transformers with Multi-Hop Attention Diffusion for Long Sequences. - Aosong Feng; Irene Li; Yuang Jiang; Rex Ying (AAAI, 2023)

Large Language Models on Wikipedia-Style Survey Generation: an Evaluation in NLP Concepts. - Fan Gao; Hang Jiang; Moritz Blum; Jinghui Lu; Yuang Jiang; Irene Li (CoRR, 2023)

Model Pruning Enables Efficient Federated Learning on Edge Devices. - Yuang Jiang; Shiqiang Wang 001; Víctor Valls; Bong Jun Ko; Wei-Han Lee; Kin K. Leung; Leandros Tassiulas (IEEE Trans. Neural Networks Learn. Syst., 2023)

Evaluating Large Language Models on Wikipedia-Style Survey Generation. - Fan Gao; Hang Jiang; Rui Yang; Qingcheng Zeng; Jinghui Lu; Moritz Blum; Tianwei She; Yuang Jiang; Irene Li (ACL (Findings), 2024)

Leveraging Large Language Models for Concept Graph Recovery and Question Answering in NLP Education. - Rui Yang; Boming Yang; Sixun Ouyang; Tianwei She; Aosong Feng; Yuang Jiang; Freddy Lécué; Jinghui Lu; Irene Li (CoRR, 2024)

Graphusion: Leveraging Large Language Models for Scientific Knowledge Graph Fusion and Construction in NLP Education. - Rui Yang; Boming Yang; Sixun Ouyang; Tianwei She; Aosong Feng; Yuang Jiang; Freddy Lécué; Jinghui Lu; Irene Li (CoRR, 2024)

SplitLLM: Collaborative Inference of LLMs for Model Placement and Throughput Optimization. - Akrit Mudvari; Yuang Jiang; Leandros Tassiulas (CoRR, 2024)

Graphusion: A RAG Framework for Knowledge Graph Construction with a Global Perspective. - Rui Yang; Boming Yang; Aosong Feng; Sixun Ouyang; Moritz Blum; Tianwei She; Yuang Jiang; Freddy Lécué; Jinghui Lu; Irene Li (CoRR, 2024)

Graphusion: A RAG Framework for Scientific Knowledge Graph Construction with a Global Perspective. - Rui Yang; Boming Yang; Xinjie Zhao 004; Fan Gao; Aosong Feng; Sixun Ouyang; Moritz Blum; Tianwei She; Yuang Jiang; Freddy Lécué; Jinghui Lu; Irene Li (WWW (Companion Volume), 2025)

MKG-Rank: Enhancing Large Language Models with Knowledge Graph for Multilingual Medical Question Answering. - Feiyang Li; Yingjian Chen; Haoran Liu; Rui Yang; Han Yuan; Yuang Jiang; Tianxiao Li; Edison Marrese-Taylor; Hossein Rouhizadeh; Yusuke Iwasawa; Douglas Teodoro; Yutaka Matsuo; et al. (CoRR, 2025)