Kai-Wei Chang
Short Bio:
I am an associate professor at UCLA and an Amazon Scholar at Alexa AI. My research interests are twofold:
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Trustworthy NLP: we published pioneering works on aligning NLP models with human values focusing on fairness in NLU and generative AI, as well as enhancing their robustness. I orgainze Trustworthy NLP workshops at NAACL/ACL.
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Multimodal Foundation Models: we developed VisualBERT, one of the first vision-language models, and SOTA VL models, including GLIP and DesCo, that can recognize objects through langauge descriptions.
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Reasoning in NLP: We developed a method enabling LLMs to adhere to specified constraints. Additionally, we study the commonsense, mathematical, and logical reasoning capabilities of LLMs.
I was selected as a Sloan Fellow (2021), AAAI senior member (2023). Several papers from our team are top-10 cited papers at AI conferences, and some received awards, such as Best Paper in EMNLP (2017), KDD (2010) and Oustanding Paper at ACL (2023). My research is supported by NSF, IARPA, ONR, NIH, and DARPA as well as industrial partners, including Taboola, Amazon, Facebook, CISCO, OptumLabs, and Google.
Join us! We are looking for prospective students and postdocs, please read this.
UCLA Natural Language Processing Group (see our members)
Selected Recent Papers
- Publications sorted by topics and year
- Google Scholar.
- VideoCon: Robust video-language alignment via contrast captions, Hritik Bansal, Yonatan Bitton, Idan Szpektor, Kai-Wei Chang, and Aditya Grover, in CVPR, 2024. Details
- Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models, Pan Lu, Baolin Peng, Hao Cheng, Michel Galley, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, and Jianfeng Gao, in NeurIPS, 2023. Details
- DesCo: Learning Object Recognition with Rich Language Descriptions, Liunian Harold Li, Zi-Yi Dou, Nanyun Peng, and Kai-Wei Chang, in NeurIPS, 2023. Details
- Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation, Da Yin, Xiao Liu, Fan Yin, Ming Zhong, Hritik Bansal, Jiawei Han, and Kai-Wei Chang, in EMNLP, 2023. Details
- Kelly is a Warm Person, Joseph is a Role Model: Gender Biases in LLM-Generated Reference Letters, Yixin Wan, George Pu, Jiao Sun, Aparna Garimella, Kai-Wei Chang, and Nanyun Peng, in EMNLP-Findings, 2023. Details
- CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning, Hritik Bansal, Nishad Singhi, Yu Yang, Fan Yin, Aditya Grover, and Kai-Wei Chang, in ICCV, 2023. Details
- Controllable Text Generation with Neurally-Decomposed Oracle, Tao Meng, Sidi Lu, Nanyun Peng, and Kai-Wei Chang, in NeurIPS, 2022. Details
- Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning, Da Yin, Liunian Harold Li, Ziniu Hu, Nanyun Peng, and Kai-Wei Chang, in EMNLP, 2021. Details
- Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies, Sunipa Dev, Masoud Monajatipoor, Anaelia Ovalle, Arjun Subramonian, Jeff Phillips, and Kai-Wei Chang, in EMNLP, 2021. Details
- Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints, Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang, in EMNLP, 2017. Details
Selected Awards
- Sloan Research Fellowship, 2021
- Okawa Research Grant Award, 2018
- EMNLP Best Long Paper Award, 2017
- KDD Best Paper Award, 2010
- Amazon Research Award, Facebook Research Award
Selected Talks/Tutorials
- Tutorial: Indirectly Supervised Natural Language Processing
- Tutorial: Robustness and Adversarial Examples in NLP
- Tutorial: Recent Advances in Transferable Representation Learning
- Tutorial: Bias and Fairness in Natural Language Processing
- Tutorial: Learning and Inference in Structured Prediction Models
- Tutorial: Hands-on Tutorial: Quantifying and Reducing Gender Stereotypes in Word Embeddings
About Me
Experience (CV)
- Associate Professor, UCLA Computer Science 22-
- Assistant Professor, UCLA Computer Science 17-22
- Assistant Professor, U.Va. Computer Science 16-17
- Amazon Scholar, Amazon AGI 23-
- Amazon Visting Academics, Amazon AGI 20-23
- Post-doc, Microsoft Research New England 15-16
- Ph.D., UIUC Computer Science 15
- M.S. (Computer Science), B.S. (Computer Science), B.S. (Electrical Engineering), National Taiwan University
Teaching
- Special Topic in AI: Fairness, Accountability, and Transparency in Natural Language Processing, UCLA (Winter 2020)
- Introduction to Machine Learning, UCLA (Winter 2018, Fall 2018, Fall 2019)
- Seminar: Machine Learning in Natural Language Processing, UCLA (Fall 2017, Spring 2019)
- Advanced ML – Structured Prediction and Deep Learning, U.Va. (Spring 2017)
- Natural Language Processing, U.Va. (Fall 2016)
Service
- VP-Elect, SIGDAT (organizer of EMNLP), 2024
- Associate Program Chair: AAAI 23
- Ethics Committee Chair: NAACL 22
- Associate Editor: JMLR (24 -), JAIR (23 -), ARR, TACL (24 -)
- Senior Area Chair: NAACL, ACL, EMNLP, NeurIPS, ICML, ICLR, AAAI (since 2021)
- Orgainzer: Workshop on Trustworthy NLP NAACL 21, 22, 24, ACL 23
- Orgainzer: Workshop on Deep Structured Prediction, ICML 17
- Orgainzer: Workshop on Structured Prediction for NLP, EMNLP 16, 17
- Area Chair: NAACL 18, 19, 22 EMNLP 19, 20, 22, 23 ACL 19, 20, 21, 22, 23 AAAI 20, 21, 22, ICML 23, Neurip 22, 23, ICLR 23.
- Senior PC: AAAI 18, AAAI 19, ICML 20, IJCAI 20, 21.
- Reviwer: NAACL/ACL/EMNLP/CoNLL (since 2013); EMNLP 2018 Best Reviewer. AAAI/ICML/NeurIPS (since 2013).
- JAIR Editorial Board (19-22)
- Handbook Chair, EMNLP 18 /div>