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researcher

Lin Zhong

4 papers hereh-index 3289 citations7 works total

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

author position
  • last author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.RO2
  • cs.CL1
  • cs.SE1
same name
  • Lin Zhong — 19 papers, h 45
  • Lin Zhong — 8 papers, h 7
  • Lin Zhong — 5 papers, h 3
  • Lin Zhong — 5 papers, h 4
  • Lin Zhong — 3 papers, h 3
  • Lin Zhong — 2 papers

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

activity
20232026
most citedPrompt Cache: Modular Attention Reuse for Low-Latency Inference

12 citations · 19 across the 4 of their papers we have counts for

collaborators

4 papers

cs.SE2026

TypeGo: An OS Runtime for Embodied Agents

Guojun Chen, Alex Schott, Lin Zhong

Large language models (LLMs) can plan behavior for embodied agents from natural language, but treating the LLM as a request/response oracle on the critical path is fundamentally at…

cs.RO2024

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications

Neiwen Ling, Guojun Chen, Lin Zhong

Large Language Models (LLMs) such as GPT-4 and Llama3 can already comprehend complex commands and process diverse tasks. This advancement facilitates their application in controlli…

cs.RO2023★ 7 cited

TypeFly: Flying Drones with Large Language Model

Guojun Chen, Xiaojing Yu, Neiwen Ling +1

Recent advancements in robot control using large language models (LLMs) have demonstrated significant potential, primarily due to LLMs' capabilities to understand natural language…

cs.CL2023★ 12 cited

Prompt Cache: Modular Attention Reuse for Low-Latency Inference

In Gim, Guojun Chen, Seung-seob Lee +3

We present Prompt Cache, an approach for accelerating inference for large language models (LLM) by reusing attention states across different LLM prompts. Many input prompts have ov…

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