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Event

Media Lab @ NeurIPS 2024

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Photo by Mike Benna on Unsplash

Photo by Mike Benna on Unsplash

Tuesday — Sunday
December 10, 2024 —
December 15, 2024

The following Media Lab researchers participated in NeurIPS 2024, the 38th conference on Neural Information Processing Systems. The  conference, which is being held in a hybrid format (Vancouver, Canada and online), fosters the exchange of research advances in artificial intelligence and machine learning.

How to Optimize What Matters Most?

Rosalind W. Picard
Invited talk on what we've learned about how to build optimal AI to engineer a better future for all people. Read more on the talk event page.

Articulatory Synthesis of Speech and Diverse Vocal Sounds via Optimization

Luke Mo, Manuel Cherep, Nikhil Singh, Quinn Langford, and  Patricia Maes
Workshop on Audio Imagination: NeurIPS 2024 Workshop AI-Driven Speech, Music, and Sound Generation
Read the paper here

Autonoetic Intelligence: A Human-AI System for Intertemporal Perspective Taking

Peggy Yin, Pat Pataranutaporn, Kavin Winson, Auttasak Lapapirojn, Pichayoot Ouppaphan, Monchai Lertsutthiwong, Thanawit Prasongpongchai, Patricia Maes, and Hal Hershfield
Creative AI Session

Consent in Crisis: The Rapid Decline of the AI Data Commons

Shayne Longpre, Robert Mahari, William Brannon, Nayan Saxena, Naana Obeng-Marnu, Tobin South,  Nikhil Singh, Manuel Cherep, Jad Kabbara, Alex "Sandy" Pentland, et al. 
Poster session
Read the paper here

Data Acquisition via Experimental Design for Data Markets

Charles Lu, Baihe Huang, Sai Praneeth Karimireddy, Praneeth Vepakomma, Michael Jordan, and Ramesh Raskar
Poster session
Read the paper here

*Charles Lu also served as a reviewer for NeurIPS 2024 (Main Track and Datasets + Benchmarks Track)

HEMM: Holistic Evaluation of Multimodal Foundation Models

Paul Pu Liang, Akshay Goindani, Talha Chafekar, Leena Mathur, Haofei Yu, Ruslan Salakhutdinov, and Louis-Philippe Morency
Poster session
Read the paper here

LLM Targeted Underperformance Disproportionately Impacts Vulnerable Users

Elinor Poole-Dayan, Deb Roy, and Jad Kabbara
Workshop on Safe Generative AI
Read the paper here

MDAgents: An Adaptive Collaboration of LLMs for Medical Decision-Making

Yubin Kim, Chanwoo Park, Hyewon Jeong, Yik Siu Chan, Xuhai Xu, Daniel McDuff, Hyeonhoon Lee, Marzyeh Ghassemi, Cynthia Breazeal, and Hae Won Park
Oral session
Poster session
Read the paper here

OpenOpenAI and Alternate Altman: Democratizing the Future of AI through Speculative Participatory Media

Gauri Agarwal, Kevin Dunnell, Pat Pataranutaporn, Andrew Lippman, and Patricia Maes
Creative AI Session

Superficial Alignment, Subtle Divergence, and Nudge Sensitivity in LLM Decision-Making

Manuel Cherep, Nikhil Singh, and Patricia Maes
Workshop on Behavioral Machine Learning
Read the paper here

Text2Tradition: From Epistemological Tensions to AI-Mediated Cross-Cultural Co-Creation

Pat Pataranutaporn, Chayapatr Archiwaranguprok, Phoomparin Mano, Piyaporn Bhongse-tong, Patricia Maes, and Pichet Klunchun
Creative AI Session

Verifiable evaluations of machine learning models using zkSNARKs

Tobin South, Alexander Camuto, Shrey Jain , Robert Mahari, Christian Paquin, Jason Morton, and Alex "Sandy" Pentland
Workshop on Algorithmic Fairness through the lens of Metrics and Evaluation
Read the paper here

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