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Ion Stoica

4 papers hereh-index 7509 citations10 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.LG1
  • eess.SY1
  • stat.ML1
same name
  • Ion Stoica — 68 papers, h 41
  • Ion Stoica — 33 papers, h 17
  • Ion Stoica — 26 papers, h 10
  • Ion Stoica — 18 papers, h 18
  • Ion Stoica — 12 papers, h 5
  • Ion Stoica — 11 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedTeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models

33 citations · 36 across the 4 of their papers we have counts for

collaborators

4 papers

stat.ML2024

A Statistical Framework for Ranking LLM-Based Chatbots

Siavash Ameli, Siyuan Zhuang, Ion Stoica +1

Large language models (LLMs) have transformed natural language processing, with frameworks like Chatbot Arena providing pioneering platforms for evaluating these models. By facilit…

cs.AI2024★ 3 cited

JudgeBench: A Benchmark for Evaluating LLM-based Judges

Sijun Tan, Siyuan Zhuang, Kyle Montgomery +5

LLM-based judges have emerged as a scalable alternative to human evaluation and are increasingly used to assess, compare, and improve models. However, the reliability of LLM-based…

eess.SY2021

Composing MPC with LQR and Neural Network for Amortized Efficiency and Stable Control

Fangyu Wu, Guanhua Wang, Siyuan Zhuang +4

Model predictive control (MPC) is a powerful control method that handles dynamical systems with constraints. However, solving MPC iteratively in real time, i.e., implicit MPC, rema…

cs.LG2021★ 33 cited

TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models

Zhuohan Li, Siyuan Zhuang, Shiyuan Guo +4

Model parallelism has become a necessity for training modern large-scale deep language models. In this work, we identify a new and orthogonal dimension from existing model parallel…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.