I am a passionate AI researcher with a strong sense of responsibility for making the future a better place. I am currently pursuing my PhD (2023-2027 expected) under the joint supervision of Prof Elliott Ash & Prof Mrinmaya Sachan at ETH, and Prof Markus Leippold at UZH. I divide my time equally between both institutions.
My research focuses on NLP applications for social good. Specifically, I am dedicated to advancing two areas: (1) Fighting misinformation (with a specific interest in scientific communications). This involves claim detection, evidence retrieval, and fact-checking. (2) NLP for climate change, where I am working on creating NLP tools that enhance the transparency and comprehension of climate risks, regulations, and corporate disclosures.
I am also interested in other areas of responsible AI/NLP for social good, such as causal NLP, which contributes to the robustness, interpretability, and fairness of NLP models, and AI alignment, which ensures the reliability and safety of NLP models. I like to shoot for the moon, but I always have my feet on the ground too.
Feel free to contact me if you are seeking colaborations in the aforementioned fields.
PhD Student in NLP
Email: jingweini8@gmail.com
Department of Humanities, Social and Political Sciences
ETH Zürich
IFW-E-44, Haldeneggsteig 4
&
Department of Banking and Finance
University of Zürich
PLR-J-101, Plattenstr. 14
Events
- Organized the first ClimateNLP workshop at ACL2024, Bangkok. See Proceedings and Workshop Website.
Publications
- DIRAS: Efficient LLM-Assisted Annotation of Document Relevance in Retrieval Augmented Generation Jingwei Ni, Tobias Schimanski, Meihong Lin, Mrinmaya Sachan, Elliott Ash, Markus Leippold
- ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures (EMNLP 2024 Main) Tobias Schimanski, Jingwei Ni, Roberto Spacey, Nicola Ranger, Markus Leippold
- Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering (ACL 2024 Main) Tobias Schimanski*, Jingwei Ni*, Mathias Kraus, Elliott Ash, Markus Leippold
- AFaCTA: Assisting the Annotation of Factual Claim Detection with Reliable LLM Annotators (ACL 2024 Main) Jingwei Ni, Minjing Shi, Dominik Stammbach, Mrinmaya Sachan, Elliott Ash, Markus Leippold
- Automated Fact-Checking of Climate Change Claims with Large Language Models Markus Leippold, Saeid Ashraf Vaghefi, Dominik Stammbach, Veruska Muccione, Julia Bingler, Jingwei Ni, Chiara Colesanti-Senni, Tobias Wekhof, Tobias Schimanski, Glen Gostlow, Tingyu Yu, Juerg Luterbacher, Christian Huggel
- Exploring Nature: Datasets and Models for Analyzing Nature-Related Disclosures (AAAI 2024 Workshop on AI in Finance for Social Impact) Tobias Schimanski, Chiara Colesanti Senni, Glen Gostlow, Jingwei Ni, Tingyu Yu, Markus Leippold
- CHATREPORT: Democratizing Sustainability Disclosure Analysis through LLM-based Tools (EMNLP 2023 Demo) Jingwei Ni, Julia Bingler, Chiara Colesanti-Senni, Mathias Kraus, Glen Gostlow, Tobias Schimanski, Dominik Stammbach, Saeid Ashraf Vaghefi, Qian Wang, Nicolas Webersinke, Tobias Wekhof, Tingyu Yu, Markus Leippold
- When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLP (ACL 2023 Main) Jingwei Ni, Zhijing Jin, Qian Wang, Mrinmaya Sachan, Markus Leippold
- ChatClimate: Grounding Conversational AI in Climate Science (Nature Communications Earth & Environment) Saeid Ashraf Vaghefi, Qian Wang, Veruska Muccione, Jingwei Ni, Mathias Kraus, Julia Bingler, Tobias Schimanski, Chiara Colesanti-Senni, Nicolas Webersinke, Christrian Huggel, Markus Leippold
- Original or translated? A causal analysis of the impact of translationese on machine translation performance (NAACL 2022 Main) Jingwei Ni, Zhijing Jin, Markus Freitag, Mrinmaya Sachan, Bernhard Schölkopf
- Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP (EMNLP 2021 Main) Zhijing Jin, Julius von Kügelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schoelkopf
Education
PhD @ ETH D-GESSETH & UZH (Mar 2023 – Present)
MSc in Data Science and Machine Learning
University College London (Sept 2021 – Sept 2022)
University of Hong Kong (Sep 2017 – Sep 2021)