Publications

Last updated on 2025-02

2025

• Renxi Wang, Honglin Mu, Liqun Ma, Lizhi Lin, Yunlong Feng, Timothy Baldwin, Xudong Han, Haonan Li, SCALAR: Scientific Citation-based Live Assessment of Long-context Academic Reasoning, preprint 2025. [paper][code]
• Zenan Zhai, Hao Li, Xudong Han, Zhenxuan Zhang, Yixuan Zhang, Timothy Baldwin, Haonan Li, RuozhiBench: Evaluating LLMs with Logical Fallacies and Misleading Premises, preprint 2025. [paper][code]
• Chengqian Gao, Haonan Li, Liu Liu, Zeke Xie, Peilin Zhao, Zhiqiang Xu, Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples, preprint 2025. [paper][code]
• Lizhi Lin, Honglin Mu, Zenan Zhai, Minghan Wang, Yuxia Wang, Renxi Wang, Junjie Gao, Yixuan Zhang, Wanxiang Che, Timothy Baldwin, Xudong Han, Haonan Li, Against The Achilles’ Heel: A Survey on Red Teaming for Generative Models, JAIR 2025. [paper][code]
• Renxi Wang, Xudong Han, Lei Ji, Shu Wang, Timothy Baldwin, Haonan Li, Toolgen: Unified tool retrieval and calling via generation, ICLR 2025. [paper][code]
• Renxi Wang, Xudong Han, Yixuan Zhang, Timothy Baldwin, Haonan Li, Learning From Failure: Integrating Negative Examples when Fine-tuning Large Language Models as Agents, NAACL 2025. [paper][code]
• Zhengzhong Liu, Bowen Tan, Hongyi Wang, Willie Neiswanger, Tianhua Tao, Haonan Li, Fajri Koto, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Liqun Ma, Liping Tang, Nikhil Ranjan, Yonghao Zhuang, Guowei He, Renxi Wang, Mingkai Deng, Robin Algayres, Yuanzhi Li, Zhiqiang Shen, Preslav Nakov, Eric Xing, LLM360 K2: Scaling Up 360-Open-Source Large Language Models, preprint 2025. [paper]

2024

• Haonan Li, Xudong Han, Zenan Zhai, Honglin Mu, Hao Wang, Zhenxuan Zhang, Yilin Geng, Shom Lin, Renxi Wang, Artem Shelmanov, Xiangyu Qi, Yuxia Wang, Donghai Hong, Youliang Yuan, Meng Chen, Haoqin Tu, Fajri Koto, Tatsuki Kuribayashi, Cong Zeng, Rishabh Bhardwaj, Bingchen Zhao, Yawen Duan, Yi Liu, Emad A Alghamdi, Yaodong Yang, Yinpeng Dong, Soujanya Poria, Pengfei Liu, Zhengzhong Liu, Xuguang Ren, Eduard Hovy, Iryna Gurevych, Preslav Nakov, Monojit Choudhury, Timothy Baldwin, Libra-leaderboard: Towards Responsible AI Through a Balanced Leaderboard of Safety and Capability, preprint 2024. [paper][website]
• Haonan Li, Xudong Han, Hao Wang, Yuxia Wang, Minghan Wang, Rui Xing, Yilin Geng, Zenan Zhai, Preslav Nakov, Timothy Baldwin, Loki: An open-source tool for fact verification, COLING Demo 2024. [paper][code]
• Shengkun Tang, Liqun Ma, Haonan Li, Mingjie Sun, Zhiqiang Shen, Bi-mamba: Towards accurate 1-bit state space models, preprint 2024. [paper]
• Stella Biderman, Hailey Schoelkopf, Lintang Sutawika, Leo Gao, Jonathan Tow, Baber Abbasi, Alham Fikri Aji, Pawan Sasanka Ammanamanchi, Sidney Black, Jordan Clive, Anthony DiPofi, Julen Etxaniz, Benjamin Fattori, Jessica Zosa Forde, Charles Foster, Mimansa Jaiswal, Wilson Y Lee, Haonan Li, Charles Lovering, Niklas Muennighoff, Ellie Pavlick, Jason Phang, Aviya Skowron, Samson Tan, Xiangru Tang, Kevin A Wang, Genta Indra Winata, François Yvon, Andy Zou, Lessons from the Trenches on Reproducible Evaluation of Language Models, preprint 2024. [paper]
• Rocktim Jyoti Das, Simeon Emilov Hristov, Haonan Li, Dimitar Iliyanov Dimitrov, Ivan Koychev, Preslav Nakov, EXAMS-V: A Multi-Discipline Multilingual Multimodal Exam Benchmark for Evaluating Vision Language Models, ACL 2024. [paper][code]
• Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, Sergey Petrakov, Haonan Li, Hamdy Mubarak, Evgenii Tsymbalov, Gleb Kuzmin, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov, Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification, ACL 2024. [paper]
• Fajri Koto, Haonan Li, Sara Shatnawi, Jad Doughman, Abdelrahman Boda Sadallah, Aisha Alraeesi, Khalid Almubarak, Zaid Alyafeai, Neha Sengupta, Shady Shehata, Nizar Habash, Preslav Nakov, Timothy Baldwin, ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic, ACL 2024. [paper][code]
• Yuxia Wang, Zenan Zhai, Haonan Li, Xudong Han, Lizhi Lin, Zhenxuan Zhang, Jingru Zhao, Preslav Nakov, Timothy Baldwin, A Chinese Dataset for Evaluating the Safeguards in Large Language Models, ACL 2024. [paper]
• Haonan Li, Yixuan Zhang, Fajri Koto, Yifei Yang, Hai Zhao, Yeyun Gong, Nan Duan, Timothy Baldwin, CMMLU: Measuring massive multitask language understanding in Chinese, ACL 2024. [paper] [code]
• Yuxia Wang*, Haonan Li*, Xudong Han*, Preslav Nakov, Timothy Baldwin, Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs, EACL 2024. [paper] [code]

2023

• Zhengzhong Liu, Aurick Qiao, Willie Neiswanger, Hongyi Wang, Bowen Tan, Tianhua Tao, Junbo Li, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Yonghao Zhuang, Guowei He, Haonan Li, Fajri Koto, Liping Tang, Nikhil Ranjan, Zhiqiang Shen, Xuguang Ren, Roberto Iriondo, Cun Mu, Zhiting Hu, Mark Schulze, Preslav Nakov, Tim Baldwin, Eric P Xing, Llm360: Towards Fully Transparent Open-source LLMs, preprint 2023. [paper][code]
• Haonan Li, Martin Tomko and Timothy Baldwin, Location Aware Modular Biencoder for Tourism Question Answering, AACL 2023. [[paper]][code]
• Yixuan Zhang, Haonan Li, Can Large Language Model Comprehend Ancient Chinese? A Preliminary Test on ACLUE, ALP 2023. [paper][code]
• Fajri Koto, Nurul Aisyah, Haonan Li, Timothy Baldwin, Large Language Models Only Pass Primary School Exams in Indonesia: A Comprehensive Test on IndoMMLU, EMNLP 2023. [paper][code]
• Haonan Li, Incorporating structured and unstructured information for geospatial question answering, Ph.D. Thesis, The University of Melbourne 2023. [Thesis]
• Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, Satheesh Katipomu, Haonan Li, Fajri Koto, Osama Mohammed Afzal, Samta Kamboj, Onkar Pandit, Rahul Pal, Lalit Pradhan, Zain Muhammad Mujahid, Massa Baali, Alham Fikri Aji, Zhengzhong Liu, Andy Hock, Andrew Feldman, Jonathan Lee, Andrew Jackson, Preslav Nakov, Timothy Baldwin, Eric Xing, Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models, preprint 2023. [paper] [website]
• Haonan Li*, Fajri Koto*, Minghao Wu, Alham Fikri Aji, Timothy Baldwin, Bactrian-X: A Multilingual Replicable Instruction-Following Model with Low-Rank Adaptation, preprint, 2023. [paper] [code]

2022

• Shuai Fan, Chen Lin, Haonan Li, Zhenghao Lin, Jinsong Su, Hang Zhang, Yeyun Gong, Jian Guo, Nan Duan, Sentiment-Aware Word and Sentence Level Pre-training for Sentiment Analysis, EMNLP 2022. [paper] [code]
• Haonan Li, Yameng Huang, Yeyun Gong, Jian Jiao, Ruofei Zhang, Timothy Baldwin, Nan Duan, CULG: Commercial Universal Language Generation, NAACL (Industry Track) 2022. [paper]
• Haonan Li, Maria Vasardani, Martin Tomko, Timothy Baldwin, MultiSpanQA: A Dataset for Multi-Span Question Answering, NAACL 2022. [paper] [website]
• Zuchao Li, Junru Zhou, Hai Zhao, Zhisong Zhang, Haonan Li, Yuqi Ju, Neural character-level syntactic parsing for Chinese, JAIR 2021. [paper]

2021

• Haonan Li, Yeyun Gong, Jian Jiao, Ruofei Zhang, Timothy Baldwin, Nan Duan, KFCNet: Knowledge Filtering and Contrastive Learning for Generative Commonsense Reasoning, 2021. [paper]
• Haonan Li, Ehsan Hamzei, Ivan Majic, Hua Hua, Jochen Renz, Martin Tomko, Maria Vasardani, Stephen Winter, Timothy Baldwin, Neural Factoid Geospatial Question Answering, JOSIS 2021. [paper] [code]
• Werner Kuhn, Ehsan Hamzei, Martin Tomko, Stephan Winter, Haonan Li, The Semantics of Place-related Questions, JOSIS 2021. [paper]

2020

• Haonan Li, Maria Vasardani, Martin Tomko, Timothy Baldwin, Target Word Masking for Location Metonymy Resolution, COLING 2020. [paper] [code]
• Ehsan Hamzei, Haonan Li, Maria Vasardani, Timothy Baldwin, Stephan Winter, Martin Tomko, Place Questions and Human-Generated Answers: A Data Analysis Approach, AGILE 2020. [paper] [code]

2019

• Haonan Li, Minghan Wang, Maria Vasardani, Martin Tomko, Timothy Baldwin, UniMelb at SemEval-2019 Task 12: Multi-model combination for toponym resolution, SevEval 2019. [paper]

2018

• Haonan Li, Zhisong Zhang, Yuqi Ju, Hai Zhao, Neural character-level dependency parsing for Chinese, AAAI 2018. [paper]