Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP. - Zhijing Jin 001; Julius von Kügelgen; Jingwei Ni; Tejas Vaidhya; Ayush Kaushal; Mrinmaya Sachan; Bernhard Schölkopf (EMNLP (1), 2021)

Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance. - Jingwei Ni; Zhijing Jin 001; Markus Freitag; Mrinmaya Sachan; Bernhard Schölkopf (NAACL-HLT, 2022)

Teachers cooperation: team-knowledge distillation for multiple cross-domain few-shot learning. - Zhong Ji; Jingwei Ni; Xiyao Liu 002; Yanwei Pang (Frontiers Comput. Sci., 2022)

When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLP. - Jingwei Ni; Zhijing Jin 001; Qian Wang; Mrinmaya Sachan; Markus Leippold (ACL (1), 2023)

CHATREPORT: Democratizing Sustainability Disclosure Analysis through LLM-based Tools. - Jingwei Ni; Julia Anna Bingler; Chiara Colesanti Senni; Mathias Kraus; Glen Gostlow; Tobias Schimanski; Dominik Stammbach; Saeid Ashraf Vaghefi; Qian Wang; Nicolas Webersinke; Tobias Wekhof; Tingyu Yu; et al. (EMNLP (Demos), 2023)

chatClimate: Grounding Conversational AI in Climate Science. - Saeid Ashraf Vaghefi; Qian Wang; Veruska Muccione; Jingwei Ni; Mathias Kraus; Julia Anna Bingler; Tobias Schimanski; Chiara Colesanti Senni; Nicolas Webersinke; Christian Huggel; Markus Leippold (CoRR, 2023)

Exploring Nature: Datasets and Models for Analyzing Nature-Related Disclosures. - Tobias Schimanski; Chiara Colesanti Senni; Glen Gostlow; Jingwei Ni; Tingyu Yu; Markus Leippold (CoRR, 2023)

AFaCTA: Assisting the Annotation of Factual Claim Detection with Reliable LLM Annotators. - Jingwei Ni; Minjing Shi; Dominik Stammbach; Mrinmaya Sachan; Elliott Ash; Markus Leippold (ACL (1), 2024)

Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering. - Tobias Schimanski; Jingwei Ni; Mathias Kraus; Elliott Ash; Markus Leippold (ACL (1), 2024)

ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures. - Tobias Schimanski; Jingwei Ni; Roberto Martín; Nicola Ranger; Markus Leippold (EMNLP, 2024)

Automated Fact-Checking of Climate Change Claims with Large Language Models. - Markus Leippold; Saeid Ashraf Vaghefi; Dominik Stammbach; Veruska Muccione; Julia Anna Bingler; Jingwei Ni; Chiara Colesanti Senni; Tobias Wekhof; Tobias Schimanski; Glen Gostlow; Tingyu Yu; Jürg Luterbacher; et al. (CoRR, 2024)

ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures. - Tobias Schimanski; Jingwei Ni; Roberto Spacey; Nicola Ranger; Markus Leippold (CoRR, 2024)

DIRAS: Efficient LLM-Assisted Annotation of Document Relevance in Retrieval Augmented Generation. - Jingwei Ni; Tobias Schimanski; Meihong Lin; Mrinmaya Sachan; Elliott Ash; Markus Leippold (CoRR, 2024)

DIRAS: Efficient LLM Annotation of Document Relevance for Retrieval Augmented Generation. - Jingwei Ni; Tobias Schimanski; Meihong Lin; Mrinmaya Sachan; Elliott Ash; Markus Leippold (NAACL (Long Papers), 2025)

Navigating the Helpfulness-Truthfulness Trade-Off with Uncertainty-Aware Instruction Fine-Tuning. - Tianyi Wu; Jingwei Ni; Bryan Hooi; Jiaheng Zhang; Elliott Ash; See-Kiong Ng; Mrinmaya Sachan; Markus Leippold (CoRR, 2025)

LEXam: Benchmarking Legal Reasoning on 340 Law Exams. - Yu Fan; Jingwei Ni; Jakob Merane; Etienne Salimbeni; Yang Tian; Yoan Hermstrüwer; Yinya Huang; Mubashara Akhtar; Florian Geering; Oliver Dreyer; Daniel Brunner; Markus Leippold; et al. (CoRR, 2025)

Can Large Language Models Capture Human Annotator Disagreements? - Jingwei Ni; Yu Fan; Vilém Zouhar; Donya Rooein; Alexander Miserlis Hoyle; Mrinmaya Sachan; Markus Leippold; Dirk Hovy; Elliott Ash (CoRR, 2025)

Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification. - Chenfei Xiong; Jingwei Ni; Yu Fan; Vilém Zouhar; Donya Rooein; Lorena Calvo-Bartolomé; Alexander Miserlis Hoyle; Zhijing Jin 001; Mrinmaya Sachan; Markus Leippold; Dirk Hovy; Mennatallah El-Assady; et al. (CoRR, 2025)