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Is a picture of a bird a bird? A mixed-methods approach to understanding diverse human perspectives and ambiguity in machine vision models aclanthology.org/2024.nlperspec… By Alicia Parrish, Susan Hao, Sarah Laszlo, Lora Aroyo (2/17)

Learn how the Adversarial Nibbler challenge provides the holistic evaluation of gen text-to-image model robustness against harmful image generation & long-tail safety issues, by using community-driven red teaming to build a diverse set of harmful prompts. goo.gle/3X2D9Ik

Proud to be part of this effort supported by MLCommons Hugging Face and Kaggle together with an amazing team of researchers and engineers across academic and industrial organizations Vijay Janapa Reddi Alicia Parrish Oana Inel Hannah Rose Kirk Jessica Quaye Max Bartolo Charvi Rastogi

I'll be at #naacl2024 (NAACL HLT 2025) this week; come say hi if you are too! I'll be presenting this paper on measuring (sub-)group associations in annotation disagreements; joint work w/ Chris Homan Lora Aroyo Aida Davani Alicia Parrish [email protected] Mark Díaz @justaturbo & Greg Serapio-García

This is one of the many papers we have published over the last year, coming out of an amazing 2-3 year long (and ongoing) collaboration with an awesome set of collaborators within and beyond Google!

In prior work, we studied ways to disentangle disagreements in annotations along demographic lines and integrate them into ML data/model pipelines. Here, we focus on how to reliably measure distinct group-level perspectives that differ significantly from those of other groups.

More specifically, we propose GRASP, a comprehensive and extensible disagreement analysis framework to measure group association in perspectives --- considering both in-group and cross-group cohesion --- among different rater sub-groups.

This is ongoing work, and please do reach out if you have thoughts, comments, criticisms about this, or any of these papers, or thoughts on potential future collaborations.

We won OUTSTANDING PAPER at #ACL2024 for our work on evaluating values and opinions in LLMs 🥳 Thank you to the reviewers and awards committee, and again to my amazing co-authors, especially joint first author Valentin Hofmann Check out the poster + paper + full author list below 👇

Ted Chiang's latest on AI. I dont entirely agree or disagree, but he weaves a good narrative all the same. Yann LeCun for visibility. newyorker.com/culture/the-we…

Congratulations 🎉 Matt Lease

Achieving your goals is impossible without being part of a great team! It feels amazing to be in front of thousands of researchers at NeurIPS Conference, knowing there are outstanding people who have your back.

Jakub Tomczak NeurIPS Conference Danielle Belgrave Ulrich Paquet Lora Aroyo Francesco Locatello Congrats! You've all done an amazing job organizing (the yet again largest) NeurIPS this year 👏 Was great to peek a bit behind the curtain at the VIP reception today 😁 What a momentous effort!

Working with Lora Aroyo and Lingjuan Lyu to make this talk and this year’s track happen has been wonderfully rewarding!

📢 Join Google DeepMind's DEER team & shape the future of #ResponsibleAI! We're hiring a #ResearchScientist (Fixed Term Contract, 12 month) to tackle fairness in multi-modal AI. Make a real-world impact! Apply by Feb 7th: boards.greenhouse.io/deepmind/jobs/… Alicia Parrish

feeling pretty excited about being part of Expanding AI Overviews and introducing AI Mode @google blog.google/products/searc…

Amazing!! Congratulations Chris Welty !!

Preparing a dataset for NeurIPS Conference? Check out Croissant-integrated repositories like Kaggle Datasets to streamline metadata generation. Let’s set a new standard for dataset contributions!

I'm excited about the updates to dataset submission requirements and best practices we introduced this year!!!