Chris Callison-Burch

Chris Callison-Burch
BornMay 1977 (age 49)
United States
CitizenshipAmerican
Education
Known forMachine translation, Paraphrase generation, Large language models
Awards
Scientific career
FieldsNatural language processing, Artificial intelligence, Crowdsourcing
WorkplacesUniversity of Pennsylvania, Johns Hopkins University, Allen Institute for AI
ThesisParaphrasing and Translation (2003)
Miles Osborne and Mark Steedman
Websitehttps://www.cis.upenn.edu/~ccb/

Chris Callison-Burch is an American computer scientist and professor of computer and information science at the University of Pennsylvania (Penn), specializing in natural language processing (NLP), artificial intelligence (AI), and crowdsourcing. He is recognised for his contributions to machine translation, paraphrase generation, and the application of large language models (LLMs) to AI challenges, with over 200 publications cited more than 33,000 times. Callison-Burch has influenced public policy on AI and copyright, testifying before the U.S. Congress in 2023 on generative AI’s implications. He serves as the faculty director for Penn’s Online Master of Science in Engineering in AI program.

Education

Callison-Burch earned his PhD in Computer Science from the University of Edinburgh in 2008, focusing on machine translation and paraphrasing techniques. His doctoral research developed statistical methods for generating paraphrases in machine translation systems, laying the foundation for his later NLP work. Prior to his PhD, he studied at Stanford University, where he developed an interest in computational linguistics.

Career

After his PhD, Callison-Burch joined the Centre for Language and Speech Processing at Johns Hopkins University as a research faculty member from 2008 to 2013, working on NLP projects, including machine translation and crowdsourcing for creating training data. In 2013, he joined the University of Pennsylvania as an assistant professor in the Department of Computer and Information Science and was promoted to associate professor in 2017, and to full professor in 2024.

At Penn, Callison-Burch teaches courses on AI and NLP, including CIS 5300 (Natural Language Processing) and CIS 5210 (Artificial Intelligence), which attract over 500 students annually. He directs Penn’s Online Master of Science in Engineering in AI program, launched in 2025. He teaches AI and NLP courses on Coursera, reaching thousands of global learners.

Callison-Burch was a part-time visiting researcher at Google in 2019 and 2020, where he collaborated on applying Google's LLM to Dungeons & Dragons dialogues. In 2023, he took a sabbatical at the Allen Institute for AI (AI2), where he contributed to vision-language models.

Research

Callison-Burch’s research focuses on NLP, AI, and crowdsourcing, with significant contributions to machine translation, paraphrase generation, and LLMs for tasks like text simplification and bias detection. His early work developed crowdsourcing methods for machine translation, leveraging non-expert annotators for paraphrase-based evaluation, influencing platforms like Amazon Mechanical Turk.

Recent projects have included several notable works. Molmo and PixMo (2025) are open-weight vision-language models developed with AI2, achieving state-of-the-art multimodal performance and earning a Best Paper Honourable Mention at CVPR 2025. Also in 2025, his work on Calibrating Large Language Models with Sample Consistency improves LLM reliability via sample-based calibration, presented at NAACL 2025. The Media Bias Detector (2025) is a real-time tool analysing selection and framing bias in news, using LLMs to detect persuasive language differences (e.g., Russian vs. English Wikipedia). Holodeck (2024) is a language-guided system for generating 3D embodied AI environments, presented at CVPR 2024. BORDIRLINES (2024) is a dataset for cross-lingual retrieval-augmented generation, focusing on culturally sensitive tasks.

He has co-authored over 200 publications, featured at conferences like ACL, EMNLP, and CVPR.

Awards and recognition

Callison-Burch has received numerous awards:

He has received research funding from Google, Microsoft, Amazon, Facebook, Roblox, DARPA, IARPA, and NSF. His h-index is 72, with over 33,000 citations. He served as General Chair of ACL 2017 and as the Program Co-Chair EMNLP 2015.

Public policy and testimony

On May 17, 2023, Callison-Burch testified before the U.S. House Subcommittee on Courts, Intellectual Property, and the Internet on AI and copyright law. His testimony emphasised generative AI’s role in creative industries and the need for balanced copyright frameworks. He has appeared on Fox News to discuss AI’s societal impact, and discussed its impact with other print news sources.

He contributes to AI ethics discussions, including workshops on AI’s effects on writing and creative professions.

See also

References

  1. ↑ "Chris Callison-Burch earns $50,000 Slone Research Fellowship". Magnolia Reporter - Magnolia, Arkansas News. 19 February 2014.
  2. 1 2 3 4 5 6 7 8 "Chris Callison-Burch". University of Pennsylvania Department of Computer and Information Science. Retrieved September 14, 2025.
  3. 1 2 3 4 5 "Chris Callison-Burch - Google Scholar". Google Scholar. Retrieved September 14, 2025.
  4. 1 2 3 4 5 6 "Online Master of Science in Engineering in Artificial Intelligence". University of Pennsylvania. Retrieved September 14, 2025.
  5. 1 2 3 4 5 "Chris Callison-Burch - ACL Anthology". ACL Anthology. Retrieved September 14, 2025.
  6. ↑ "Chris Callison-Burch". www.cis.upenn.edu. Retrieved 2025-09-14.
  7. 1 2 3 "Testimony of Chris Callison-Burch Before the U.S. House Subcommittee on Courts, Intellectual Property, and the Internet" (PDF). U.S. House of Representatives. 2023-05-17. Retrieved September 14, 2025.
  8. ↑ Kim, Rachel (2024-01-03). "AI and Copyright Law in 2023: Federal Government Activities". Copyright Alliance. Retrieved 2025-09-14.
  9. 1 2 "Chris Callison-Burch". www.cis.upenn.edu. Retrieved 2025-09-14.
  10. 1 2 3 Callison-Burch, Chris (2007). "Paraphrasing with Bilingual Parallel Corpora" (PDF). Proceedings of ACL 2007. Retrieved September 14, 2025.
  11. ↑ "Improved Statistical Machine Translation Using Paraphrases - Chris Callison-Burch (University of Edinburgh)". Center for Language and Speech Processing. Retrieved 2025-09-14.
  12. ↑ "Chris Callison-Burch | ILST". web.sas.upenn.edu. Retrieved 2025-09-14.
  13. ↑ "Former Faculty". Center for Language and Speech Processing. Retrieved 2025-09-14.
  14. 1 2 "New Online AI Master's Program at Penn". Penn Today. 2023-04-20. Retrieved September 14, 2025.
  15. ↑ "Chris Callison-Burch". callison-burch.github.io. Retrieved 2025-09-14.
  16. ↑ Huffman, Sarah (2024-04-30). "Penn Engineering rolls out an online master's degree in artificial intelligence". Technical.ly. Retrieved 2025-09-14.
  17. ↑ "Meet Chris Callison-Burch, MSE-AI Online Program Director". 3 May 2024. Retrieved 2025-09-14.
  18. ↑ "Chris Callison-Burch on Coursera". Coursera. Retrieved September 14, 2025.
  19. ↑ "Chris Callison-Burch". www.cis.upenn.edu. Retrieved 2025-09-14.
  20. ↑ Callison-Burch, Chris; Tomar, Gaurav Singh; Martin, Lara J.; Ippolito, Daphne; Bailis, Suma; Reitter, David (2022). "Dungeons and Dragons as a Dialog Challenge for Artificial Intelligence". Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Abu Dhabi, United Arab Emirates: Association for Computational Linguistics: 9379–9393. doi:10.18653/v1/2022.emnlp-main.637.
  21. ↑ "Open source tool helps vision-language models 'see' more clearly". optics.org. Retrieved 2025-09-14.
  22. 1 2 "Chris Callison-Burch". callison-burch.github.io. Retrieved 2025-09-14.
  23. ↑ Deitke, Matt; Clark, Christopher; Lee, Sangho; Tripathi, Rohun; Yang, Yue; Park, Jae Sung; Salehi, Mohammadreza; Muennighoff, Niklas; Lo, Kyle (2024-12-05). "Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models". arXiv:2409.17146 [cs.CV].
  24. ↑ Wang, Jenny S.; Haider, Samar; Tohidi, Amir; Gupta, Anushkaa; Zhang, Yuxuan; Callison-Burch, Chris; Rothschild, David; Watts, Duncan J. (2025-04-28). "Media Bias Detector: Designing and Implementing a Tool for Real-Time Selection and Framing Bias Analysis in News Coverage". Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. pp. 1–27. arXiv:2502.06009. doi:10.1145/3706598.3713716. ISBN 979-8-4007-1394-1.
  25. ↑ Callison-Burch, Chris (2009). "Fast, Cheap, and Creative: Evaluating Translation Quality Using Amazon's Mechanical Turk" (PDF). Proceedings of EMNLP 2009. Retrieved September 14, 2025.
  26. 1 2 Callison-Burch, Chris (2011). "Crowdsourcing Translation: Professional Quality from Non-Professionals" (PDF). Proceedings of ACL 2011. Retrieved September 14, 2025.
  27. 1 2 "Molmo and PixMo: Open Weight Vision-Language Models". Allen Institute for AI. 2025-01-15. Retrieved September 14, 2025.
  28. ↑ "Paper page - Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models". huggingface.co. 2024-09-26. Retrieved 2025-09-14.
  29. 1 2 Callison-Burch, Chris (2025). "Molmo: Open Weight Vision-Language Models". Proceedings of CVPR 2025. arXiv:2409.17146.
  30. ↑ Deitke, Matt; Clark, Christopher; Lee, Sangho; Tripathi, Rohun; Yang, Yue; Park, Jae Sung; Salehi, Mohammadreza; Muennighoff, Niklas; Lo, Kyle; Soldaini, Luca; Lu, Jiasen; Anderson, Taira; Bransom, Erin; Ehsani, Kiana; Ngo, Huong (2025). "Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models". 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 91–104. arXiv:2409.17146. doi:10.1109/CVPR52734.2025.00018. ISBN 979-8-3315-4364-8.
  31. ↑ Lyu, Qing; Shridhar, Kumar; Malaviya, Chaitanya; Zhang, Li; Elazar, Yanai; Tandon, Niket; Apidianaki, Marianna; Sachan, Mrinmaya; Callison-Burch, Chris (2025-08-05). "Calibrating Large Language Models with Sample Consistency". Proceedings of the AAAI Conference on Artificial Intelligence. AAAI'25/IAAI'25/EAAI'25. 39 (18). AAAI Press: 19260–19268. arXiv:2402.13904. doi:10.1609/aaai.v39i18.34120. ISBN 978-1-57735-897-8.{{cite journal}}: CS1 maint: periodical has ISBN (link)
  32. ↑ Callison-Burch, Chris (2025). "Calibrating LLMs with Sample Consistency". Proceedings of NAACL 2025. arXiv:2402.13904.
  33. ↑ "Accepted Papers". NAACL-HLT 2025. Retrieved 2025-09-14.
  34. ↑ Wang, Jenny S; Haider, Samar; Tohidi, Amir; Gupta, Anushkaa; Zhang, Yuxuan; Callison-Burch, Chris; Rothschild, David; Watts, Duncan J (2025-04-25). "Media Bias Detector: Designing and Implementing a Tool for Real-Time Selection and Framing Bias Analysis in News Coverage". Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. CHI '25. New York, NY, USA: Association for Computing Machinery. pp. 1–27. doi:10.1145/3706598.3713716. ISBN 979-8-4007-1394-1.
  35. ↑ Callison-Burch, Chris (2024). "Holodeck: Language-Guided 3D Environment Generation". Proceedings of CVPR 2024. arXiv:2312.09067.
  36. ↑ Yang, Yue; Sun, Fan-Yun; Weihs, Luca; VanderBilt, Eli; Herrasti, Alvaro; Han, Winson; Wu, Jiajun; Haber, Nick; Krishna, Ranjay; Liu, Lingjie; Callison-Burch, Chris; Yatskar, Mark; Kembhavi, Aniruddha; Clark, Christopher (2024). "Holodeck: Language Guided Generation of 3D Embodied AI Environments". 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 16227–16237. arXiv:2312.09067. doi:10.1109/CVPR52733.2024.01536. ISBN 979-8-3503-5300-6.
  37. ↑ Callison-Burch, Chris (2025). "Media Bias Detection with Large Language Models". Proceedings of EMNLP 2025. arXiv:2410.01171v1.
  38. ↑ Li, Bryan; Luo, Fiona; Haider, Samar; Agashe, Adwait; Li, Tammy; Liu, Runqi; Miao, Muqing; Ramakrishnan, Shriya; Yuan, Yuan (2025-06-22). "Multilingual Retrieval Augmented Generation for Culturally-Sensitive Tasks: A Benchmark for Cross-lingual Robustness". arXiv:2410.01171 [cs.CL].
  39. ↑ Callison-Burch, Chris (2024). "Evaluating Vision-Language Models on Bistable Images". Proceedings of CMCL 2024: 8–29. arXiv:2405.19423. doi:10.18653/v1/2024.cmcl-1.2. Retrieved September 14, 2025.
  40. ↑ Callison-Burch, Chris (2016). "So-Called Non-Subsective Adjectives". Proceedings of STARSEM 2016: 114–119. doi:10.18653/v1/S16-2014. Retrieved September 14, 2025.
  41. ↑ Callison-Burch, Chris (2017). "Word Sense Filtering Improves Embedding-Based Lexical Substitution". Proceedings of SenseRep 2017: 110–119. doi:10.18653/v1/W17-1914. Retrieved September 14, 2025.
  42. ↑ Callison-Burch, Chris (2018). "A Data-Driven Analysis of Workers' Earnings on Amazon Mechanical Turk". Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. pp. 1–14. doi:10.1145/3173574.3174023. ISBN 978-1-4503-5620-6. Retrieved September 14, 2025.
  43. 1 2 "Google Faculty Research Awards 2011". Google Research. Retrieved September 14, 2025.
  44. 1 2 "Sloan Research Fellowships". Sloan Foundation. Retrieved September 14, 2025.
  45. ↑ "AI in Academia: Chris Callison-Burch on Fox News". Fox News. 2023-07-10. Retrieved September 14, 2025.
  46. ↑ "AI and the Future of Work". CNN. 2023-08-15. Retrieved September 14, 2025.
  47. ↑ Submittable. "Cleaver Magazine - CHRIS CALLISON-BURCH: What Writers Need to Learn about AI and Large Language Models PURCHASE RECORDING". cleavermagazine.submittable.com. Retrieved 2025-09-14.