CV

CV can be downloaded from here and 这里.

Education

• Ph.D. Computer Science, Monash University, 2022
• M.Eng. Information Technology, The University of Melbourne, 2018
• B.Sc. Statistics and Information Systems, The University of Sydney, 2016

Work Experience

• Nov. 2024 - Apr. 2025: Research Intern at Alibaba Group.
• Jul. 2023 - Oct. 2023: Research Intern at Tencent AI Lab.
• Apr. 2023 - Jul. 2023: Visiting Researcher at Mohamed bin Zayed University of Artificial Intelligence.
• Jul. 2020 - Jul. 2021: Research Intern at Huawei Noah’s Ark Lab.
• Aug. 2018 - Jul. 2019: Research Engineer at JD AI Research of JD.com, Inc.

Languages

• Chinese: Native or Bilingual Proficiency
• English: Full Professional Proficiency

Publications

Learning to Summarize by Learning to Quiz: Adversarial Agentic Collaboration for Long Document Summarization

Weixuan Wang*, Minghao Wu*, Barry Haddow, and Alexandra Birch. Learning to Summarize by Learning to Quiz: Adversarial Agentic Collaboration for Long Document Summarization. abs/2509.20900.

HBO: Hierarchical Balancing Optimization for Fine-Tuning Large Language Models

Weixuan Wang*, Minghao Wu*, Barry Haddow, and Alexandra Birch. HBO: Hierarchical Balancing Optimization for Fine-Tuning Large Language Models. abs/2505.12300.

ExpertSteer: Intervening in LLMs through Expert Knowledge

Weixuan Wang*, Minghao Wu*, Barry Haddow, and Alexandra Birch. ExpertSteer: Intervening in LLMs through Expert Knowledge. abs/2505.12313.

(Perhaps) Beyond Human Translation: Harnessing Multi-Agent Collaboration for Translating Ultra-Long Literary Texts

Minghao Wu, Jiahao Xu, Yulin Yuan, Gholamreza Haffari, Longyue Wang, Weihua Luo, and Kaifu Zhang. (Perhaps) Beyond Human Translation: Harnessing Multi-Agent Collaboration for Translating Ultra-Long Literary Texts. TACL 2025

Bridging the Language Gaps in Large Language Models with Inference-Time Cross-Lingual Intervention

Weixuan Wang*, Minghao Wu*, Barry Haddow, and Alexandra Birch. Bridging the Language Gaps in Large Language Models with Inference-Time Cross-Lingual Intervention. ACL 2025 Outstanding Paper Award

The Best of Both Worlds: Bridging Quality and Diversity in Data Selection with Bipartite Graph

Minghao Wu, Thuy-Trang Vu, Lizhen Qu, Gholamreza Haffari. The Best of Both Worlds: Bridging Quality and Diversity in Data Selection with Bipartite Graph. ICML 2025

The Bitter Lesson Learned from 2,000+ Multilingual Benchmarks

Minghao Wu, Weixuan Wang, Sinuo Liu, Huifeng Yin, Xintong Wang, Yu Zhao, Chenyang Lyu, Longyue Wang, Weihua Luo, Kaifu Zhang. The Bitter Lesson Learned from 2,000+ Multilingual Benchmarks. abs/2504.15521.

Demystifying Multilingual Chain-of-Thought in Process Reward Modeling

Weixuan Wang*, Minghao Wu*, Barry Haddow, and Alexandra Birch. Demystifying Multilingual Chain-of-Thought in Process Reward Modeling. abs/2502.12663.

TransAgents: Build Your Translation Company with Language Agents

Minghao Wu, Jiahao Xu, and Longyue Wang. TransAgents: Build Your Translation Company with Language Agents. EMNLP 2024

Mixture-of-Skills: Learning to Optimize Data Usage for Fine-Tuning Large Language Models

Minghao Wu, Thuy-Trang Vu, Lizhen Qu, and Gholamreza Haffari. Mixture-of-Skills: Learning to Optimize Data Usage for Fine-Tuning Large Language Models. EMNLP 2024

LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions

Minghao Wu, Abdul Waheed, Chiyu Zhang, Muhammad Abdul-Mageed, and Alham Fikri Aji. LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions. EACL 2024

Importance-Aware Data Augmentation for Document-Level Neural Machine Translation

Minghao Wu, Yufei Wang, George Foster, Lizhen Qu, and Gholamreza Haffari. Importance-Aware Data Augmentation for Document-Level Neural Machine Translation. EACL 2024

Adapting Large Language Models for Document-Level Machine Translation

Minghao Wu, Thuy-Trang Vu, Lizhen Qu, George Foster, Gholamreza Haffari. Adapting Large Language Models for Document-Level Machine Translation. abs/2401.06468.

Document Flattening: Beyond Concatenating Context for Document-Level Neural Machine Translation

Minghao Wu, George Foster, Lizhen Qu, and Gholamreza Haffari. 2023. Document Flattening: Beyond Concatenating Context for Document-Level Neural Machine Translation. EACL 2023

Uncertainty-Aware Balancing for Multilingual and Multi-Domain Neural Machine Translation Training

Minghao Wu, Yitong Li, Meng Zhang, Liangyou Li, Gholamreza Haffari and Qun Liu (2021) Uncertainty-Aware Balancing for Multilingual and Multi-Domain Neural Machine Translation Training. EMNLP 2021

Evaluating the Utility of Hand-crafted Features in Sequence Labelling

Minghao Wu, Fei Liu and Trevor Cohn. Evaluating the Utility of Hand-crafted Features in Sequence Labelling. EMNLP 2018