Jingwei Ni

According to our database, Jingwei Ni authored at least 18 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Mrinmaya Sachan, Markus Leippold, Dirk Hovy, Mennatallah El-Assady, Elliott Ash

CoRR, July, 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, June, 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, Mrinmaya Sachan, Alexander Stremitzer, Christoph Engel, Elliott Ash, Joel Niklaus

CoRR, May, 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, February, 2025

DIRAS: Efficient LLM Annotation of Document Relevance for Retrieval Augmented Generation.

Jingwei Ni, Tobias Schimanski, Meihong Lin, Mrinmaya Sachan, Elliott Ash, Markus Leippold

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

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

ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures.

Tobias Schimanski, Jingwei Ni, Roberto Spacey, Nicola Ranger, Markus Leippold

CoRR, 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, Christian Huggel

CoRR, 2024

ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures.

Tobias Schimanski, Jingwei Ni, Roberto Martín, Nicola Ranger, Markus Leippold

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering.

Tobias Schimanski, Jingwei Ni, Mathias Kraus, Elliott Ash, Markus Leippold

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

AFaCTA: Assisting the Annotation of Factual Claim Detection with Reliable LLM Annotators.

Jingwei Ni, Minjing Shi, Dominik Stammbach, Mrinmaya Sachan, Elliott Ash, Markus Leippold

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

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

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

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, Markus Leippold

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLP.

Jingwei Ni, Zhijing Jin, Qian Wang, Mrinmaya Sachan, Markus Leippold

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Teachers cooperation: team-knowledge distillation for multiple cross-domain few-shot learning.

Zhong Ji, Jingwei Ni, Xiyao Liu, Yanwei Pang

Frontiers Comput. Sci., 2022

Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance.

Jingwei Ni, Zhijing Jin, Markus Freitag, Mrinmaya Sachan, Bernhard Schölkopf

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

2021

Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP.

Zhijing Jin, Julius von Kügelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schölkopf

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021