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researcher

Yufan Song

Carnegie Mellon University

4 papers hereh-index 51.1k citations6 works total

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

author position
  • middle author4

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

fields
  • cs.LG2
  • cs.CL1
  • cs.SE1
affiliations
  • Carnegie Mellon University
Homepage
same name
  • Yufan Song — 1 paper, h 1
  • Yufan Song — 1 paper, h 2

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
20222026
most citedEnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine

14 citations · 25 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2026

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

Weinan Dai, Hanlin Wu, Qiying Yu +13

GPU kernel optimization is fundamental to modern deep learning but remains a highly specialized task requiring deep hardware expertise. Despite strong performance in general progra…

cs.CL2024

TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks

Frank F. Xu, Yufan Song, Boxuan Li +18

We interact with computers on an everyday basis, be it in everyday life or work, and many aspects of work can be done entirely with access to a computer and the Internet. At the sa…

cs.SE2024★ 11 cited

OpenHands: An Open Platform for AI Software Developers as Generalist Agents

Xingyao Wang, Boxuan Li, Yufan Song +21

Software is one of the most powerful tools that we humans have at our disposal; it allows a skilled programmer to interact with the world in complex and profound ways. At the same…

cs.LG2022★ 14 cited

EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine

Jiayi Weng, Min Lin, Shengyi Huang +9

There has been significant progress in developing reinforcement learning (RL) training systems. Past works such as IMPALA, Apex, Seed RL, Sample Factory, and others, aim to improve…

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