Qi Qi

About

I am a Senior Research Scientist at Meta Superintelligence Labs, where I lead the Llama4 Maverick Long Context post-training. My current research focuses on long-context LLMs and long-horizon agentic reinforcement learning. I received my Ph.D. in Computer Science from the University of Iowa, advised by Professor Tianbao Yang.

Before joined UIowa, I received master degree from University of Science and Technology of China under the supervision of Prof. Thomas Weise and bachelor degree from Qingdao University of Technology. I was a research scientist intern at Netflix Research with Shervin Ardeshir and M. Hossein Taghavi, and at Apple Display Team with Mohammad Tofigh.

News

• [Apr-2026] Try Meta AI with our new Muse Spark model!
• [Apr-2025] Llama4 Released, try our new model with context length up to 10M! Link Try our product! Meta AI
• [Nov-2022] Try our new package ABSGD for handling imbalanced classification! Tutorial
• [Oct-2022] Our ABSGD achieved 1st in ResNet50 (rank 4th of 16 overall) on Stanford WILDS iWildCam! Code
• [Aug-2022] Research intern at Netflix with Shervin Ardeshir and M. Hossein Taghavi
• [Jan-2022] Invited talk at UberAI about AUPRC maximization

Selected Publications

The Llama 4 Herd: The Beginning of a New Era of Natively Multimodal AI Innovation

AI Meta (incl. Qi Qi)

Technical Report 2025 (🔥 378+ citations) / blog / demo

AdvancedIF: Rubric-based Benchmarking and Reinforcement Learning for Advancing LLM Instruction Following

Yun He, Wenzhe Li, Hejia Zhang, Songlin Li, Karishma Mandyam, Sopan Khosla, Yuanhao Xiong, Nanshu Wang, Xiaoliang Peng, Beibin Li, Shengjie Bi, Shishir G. Patil, Qi Qi, Shengyu Feng, Julian Katz-Samuels, Richard Yuanzhe Pang, Sujan Gonugondla, Hunter Lang, Yue Yu, Yundi Qian, Maryam Fazel-Zarandi, Licheng Yu, Amine Benhalloum, Hany Awadalla, Manaal Faruqui

To Appear at ACL 2026 / paper

Scaling Agent Learning via Experience Synthesis

Zhaorun Chen, Zhuokai Zhao, Kai Zhang, Bo Liu, Qi Qi, Yifan Wu, Tarun Kalluri, Sara Cao, Yuanhao Xiong, Haibo Tong, Huaxiu Yao, Hengduo Li, Jiacheng Zhu, Xian Li, Dawn Song, Bo Li, Jason Weston, Dat Huynh

The Fourteenth International Conference on Learning Representations(ICLR) 2026 / paper

Agent Learning via Early Experience

Kai Zhang, Xiangchao Chen, Bo Liu, Tianci Xue, Zeyi Liao, Zhihan Liu, Xiyao Wang, Yuting Ning, Zhaorun Chen, Xiaohan Fu, Jian Xie, Yuxuan Sun, Boyu Gou, Qi Qi, Zihang Meng, Jianwei Yang, Ning Zhang, Xian Li, Ashish Shah, Dat Huynh, Hengduo Li, Zi Yang, Sara Cao, Lawrence Jang, Shuyan Zhou, et al.

Arxiv 2025 / paper

QCRD: Quality-guided Contrastive Rationale Distillation for Large Language Models

Wei Wang, Zhaowei Li, Qi Xu, Yiqing Cai, Hang Song, Qi Qi, Ran Zhou, Zhida Huang, Tao Wang, Li Xiao

Conference on Empirical Methods in Natural Language Processing (EMNLP) 2025 / paper

AdFair-CLIP: Adversarial Fair Contrastive Language-Image Pre-training for Chest X-rays

Chenlang Yi, Zizhan Xiong, Qi Qi, Xiyuan Wei, Girish Bathla, Ching-Long Lin, Bobak Jack Mortazavi, Tianbao Yang

International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2025 / paper

GroundingGPT: Language Enhanced Multi-modal Grounding Model

Zhaowei Li, Qi Xu, Dong Zhang, Hang Song, Yiqing Cai, Qi Qi, Ran Zhou, Junting Pan, Zefeng Li, Van Tu Vu, Zhida Huang, Tao Wang

Annual Meeting of the Association for Computational Linguistics (ACL) 2024 / paper / code

ABSGD: Attentional Biased Stochastic Gradient for Imbalanced Classification

Qi Qi, Yi Xu, Rong Jin, Wotao Yin, Tianbao Yang

Transactions on Machine Learning Research (TMLR) 2023 / paper / code

Improving Identity-Robustness for Face Models

Qi Qi, Shervin Ardeshir

International Conference on Machine Learning (ICML) 2023 SCIS Workshop / paper

Stochastic Optimization of Area Under Precision-Recall Curve for Deep Learning with Provable Convergence

Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang

Conference on Neural Information Processing Systems (NeurIPS) 2021 (250+ Github Stars) / paper / code / poster / slides

RECOVER: A Practical Online Method for Distributionally Deep Robust Optimization

Qi Qi, Zhishuai Guo, Yi Xu, Rong Jin, Tianbao Yang

Conference on Neural Information Processing Systems (NeurIPS) 2021 / paper / code / poster / slides

A Simple and Effective Framework for Pairwise Deep Metric Learning

Qi Qi, Yan Yan, Xiaoyu Wang, Tianbao Yang

European Conference on Computer Vision (ECCV) 2020 / paper / code / poster / video

Stochastic optimization for DC functions and non-smooth non-convex regularizers with non-asymptotic convergence

Yi Xu, Qi Qi, Qihang Lin, Rong Jin, Tianbao Yang

International Conference on Machine Learning (ICML) 2019 / paper / code

Professional Service

Conference Reviewing: ICML / NeurIPS / ICLR / CVPR / IJCAI