Jiaqi Ma
@jiaqima.bsky.social
Assistant Professor at UIUC. Interested in Trustworthy ML, Data Attribution, GenAI Copyright.
https://jiaqima.github.io/
https://jiaqima.github.io/
And GPT5 is worse than GPT4o in writing …
August 10, 2025 at 1:34 AM
And GPT5 is worse than GPT4o in writing …
Kudos to our co-organizers Chirag Agarwal, Hima Lakkaraju, Sarah Tan, @junweideng.bsky.social, Pingbang Hu, Eileanor LaRocco, Karolina Naranjo, @shichangzh.bsky.social
August 4, 2025 at 4:19 PM
Kudos to our co-organizers Chirag Agarwal, Hima Lakkaraju, Sarah Tan, @junweideng.bsky.social, Pingbang Hu, Eileanor LaRocco, Karolina Naranjo, @shichangzh.bsky.social
Featuring an amazing line-up of speakers: @yoshuabengio.bsky.social, @yaringal.bsky.social, Dan Hendrycks, @sarahooker.bsky.social, Gary Howarth, Bo Li, Lucilla Sioli!
August 4, 2025 at 4:19 PM
Featuring an amazing line-up of speakers: @yoshuabengio.bsky.social, @yaringal.bsky.social, Dan Hendrycks, @sarahooker.bsky.social, Gary Howarth, Bo Li, Lucilla Sioli!
DCA-Bench: A Benchmark for Dataset Curation Agents: arxiv.org/pdf/2406.07275
A benchmark for data curation tasks. Key challenge is that it requires AI agents to autonomously **discover** data quality issues.
A benchmark for data curation tasks. Key challenge is that it requires AI agents to autonomously **discover** data quality issues.
arxiv.org
July 16, 2025 at 4:10 PM
DCA-Bench: A Benchmark for Dataset Curation Agents: arxiv.org/pdf/2406.07275
A benchmark for data curation tasks. Key challenge is that it requires AI agents to autonomously **discover** data quality issues.
A benchmark for data curation tasks. Key challenge is that it requires AI agents to autonomously **discover** data quality issues.
A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning: arxiv.org/pdf/2505.19281
The first data attribution method for online RL that improves sample and computational efficiency on RL applications including RLHF.
The first data attribution method for online RL that improves sample and computational efficiency on RL applications including RLHF.
arxiv.org
July 16, 2025 at 4:10 PM
A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning: arxiv.org/pdf/2505.19281
The first data attribution method for online RL that improves sample and computational efficiency on RL applications including RLHF.
The first data attribution method for online RL that improves sample and computational efficiency on RL applications including RLHF.
A Versatile Influence Function for Data Attribution with Non-Decomposable Loss: arxiv.org/pdf/2412.01335
We developed an efficient and easy-to-implement generalization of influence function applicable to machine learning objectives that are not decomposable to loss terms on individual data points.
We developed an efficient and easy-to-implement generalization of influence function applicable to machine learning objectives that are not decomposable to loss terms on individual data points.
July 16, 2025 at 4:10 PM
A Versatile Influence Function for Data Attribution with Non-Decomposable Loss: arxiv.org/pdf/2412.01335
We developed an efficient and easy-to-implement generalization of influence function applicable to machine learning objectives that are not decomposable to loss terms on individual data points.
We developed an efficient and easy-to-implement generalization of influence function applicable to machine learning objectives that are not decomposable to loss terms on individual data points.
More details about our poster sessions:
December 11, 2024 at 7:58 PM
More details about our poster sessions:
Papers:
1. dattri: A Library for Efficient Data Attribution (arxiv.org/pdf/2410.04555)
2. Most Influential Subset Selection: Challenges, Promises, and Beyond (arxiv.org/pdf/2409.18153)
Workshop: bsky.app/profile/jiaq...
1. dattri: A Library for Efficient Data Attribution (arxiv.org/pdf/2410.04555)
2. Most Influential Subset Selection: Challenges, Promises, and Beyond (arxiv.org/pdf/2409.18153)
Workshop: bsky.app/profile/jiaq...
Join us at the #RegulatableML workshop at #NeurIPS2024 to learn about AI regulations and how to operationalize them in practice.
Date: Dec 15, 2024 (East Meeting Room 13)
Time: 8:15 am - 5:30 pm
Details: regulatableml.github.io
We have an exciting schedule (a thread):
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Date: Dec 15, 2024 (East Meeting Room 13)
Time: 8:15 am - 5:30 pm
Details: regulatableml.github.io
We have an exciting schedule (a thread):
1/
December 11, 2024 at 7:58 PM
Papers:
1. dattri: A Library for Efficient Data Attribution (arxiv.org/pdf/2410.04555)
2. Most Influential Subset Selection: Challenges, Promises, and Beyond (arxiv.org/pdf/2409.18153)
Workshop: bsky.app/profile/jiaq...
1. dattri: A Library for Efficient Data Attribution (arxiv.org/pdf/2410.04555)
2. Most Influential Subset Selection: Challenges, Promises, and Beyond (arxiv.org/pdf/2409.18153)
Workshop: bsky.app/profile/jiaq...
#RegulatableML workshop is the result of a lot of hard work from our amazing team: @jiaqima.bsky.social, Chirag Agarwal Sarah Tan, Hima Lakkaraju, Usha Bhalla, @zbucinca.bsky.social, @junweideng.bsky.social, Alex Oesterling, and Shichang (Ray) Zhang.
5/5
December 11, 2024 at 7:55 PM
#RegulatableML workshop is the result of a lot of hard work from our amazing team: @jiaqima.bsky.social, Chirag Agarwal Sarah Tan, Hima Lakkaraju, Usha Bhalla, @zbucinca.bsky.social, @junweideng.bsky.social, Alex Oesterling, and Shichang (Ray) Zhang.
5/5
⭐ Get ready for an interactive session! Dawn Song and Rishi Bommasani will discuss their exciting "A Path for Science‑ and Evidence‑based AI Policy" paper. We encourage everyone to read the paper in advance to join the conversation!
Paper: understanding-ai-safety.org #AIPolicy
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Paper: understanding-ai-safety.org #AIPolicy
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A Path for Science- and Evidence-based AI Policy
understanding-ai-safety.org
December 11, 2024 at 7:55 PM
⭐ Get ready for an interactive session! Dawn Song and Rishi Bommasani will discuss their exciting "A Path for Science‑ and Evidence‑based AI Policy" paper. We encourage everyone to read the paper in advance to join the conversation!
Paper: understanding-ai-safety.org #AIPolicy
4/
Paper: understanding-ai-safety.org #AIPolicy
4/
⭐ 10 oral presentations
⭐ A poster session of 34 accepted papers
⭐ New this year! Invited speakers will hold office hours for in-person meetings in a small, intimate setting. Check the schedule for times and take advantage of this exclusive opportunity to connect with our speakers!
3/
⭐ A poster session of 34 accepted papers
⭐ New this year! Invited speakers will hold office hours for in-person meetings in a small, intimate setting. Check the schedule for times and take advantage of this exclusive opportunity to connect with our speakers!
3/
December 11, 2024 at 7:55 PM
⭐ 10 oral presentations
⭐ A poster session of 34 accepted papers
⭐ New this year! Invited speakers will hold office hours for in-person meetings in a small, intimate setting. Check the schedule for times and take advantage of this exclusive opportunity to connect with our speakers!
3/
⭐ A poster session of 34 accepted papers
⭐ New this year! Invited speakers will hold office hours for in-person meetings in a small, intimate setting. Check the schedule for times and take advantage of this exclusive opportunity to connect with our speakers!
3/
⭐ Six keynote talks: Rumman Chowdhury, @yoshuabengio.bsky.social, @peterhenderson.bsky.social , Reva Schwartz, Dawn Song, and Rishi Bommasani.
⭐ A panel discussion on AI Regulation/Governance: Gillian K. Hadfield, Wan Sie Lee, Surdas Mohit, Sella Nevo, @robreich.bsky.social, and Savannah Thais
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⭐ A panel discussion on AI Regulation/Governance: Gillian K. Hadfield, Wan Sie Lee, Surdas Mohit, Sella Nevo, @robreich.bsky.social, and Savannah Thais
2/
December 11, 2024 at 7:55 PM
⭐ Six keynote talks: Rumman Chowdhury, @yoshuabengio.bsky.social, @peterhenderson.bsky.social , Reva Schwartz, Dawn Song, and Rishi Bommasani.
⭐ A panel discussion on AI Regulation/Governance: Gillian K. Hadfield, Wan Sie Lee, Surdas Mohit, Sella Nevo, @robreich.bsky.social, and Savannah Thais
2/
⭐ A panel discussion on AI Regulation/Governance: Gillian K. Hadfield, Wan Sie Lee, Surdas Mohit, Sella Nevo, @robreich.bsky.social, and Savannah Thais
2/