ElisaFerracane
575 posts
Two awards for UT Austin papers! Salience prediction of inquisitive questions by @YatingWu96 @ritikarmangla @AlexGDimakis me @jessyjli Learning AANNs and insights about grammatical generalization in pre-training by @kanishkamisra & @kmahowald Congrats to all the awardees!
NSF and @SimonsFdn are launching two new National AI Research Institutes. Led by @UTAustin and @NorthwesternU, each institute will receive $20 million to accelerate humanity’s understanding of the universe through the development of new AI-powered tools. bit.ly/3MO5jjR
Two of our brilliant team members, Davis Liang and Elisa Ferracane, represented Abridge at ACL 2024 in Bangkok, showcasing research that pushes the boundaries of Natural Language Processing (NLP) and multilingual understanding. 🌎🌟 Davis Liang, a Staff Research Scientist at Abridge, presented Belebele, a multilingual reading comprehension dataset covering 122 language variants designed to tackle the global challenge of understanding text across diverse languages. This dataset enables direct comparison of how well models understand different languages and opens new possibilities for evaluating and discussing LLM multilinguality: aclanthology.org/2024.acl-long.… Elisa Ferracane, a Senior NLP Research Scientist at Abridge, in collaboration with lead author Sanjana Ramprasad, an Abridge research intern, shared cutting-edge research on tackling hallucination errors in LLMs, particularly in dialogue summarization. Their work introduced a new error category to better address these challenges, marking a crucial step forward as LLMs evolve: aclanthology.org/2024.acl-long.… We’re proud to have these pioneers driving innovation at Abridge, where their expertise guides us as we build the most advanced AI platform for clinical documentation. Congrats, Davis, Elisa, and Sanjana for all your outstanding work! 👏
Check out our #ACL2024NLP paper benchmarking LLMs for faithfulness on dialogue summarization. Our analysis highlights hallucination subtleties and introduces a new error category to capture LLM-specific behavior 🧵👇 arxiv.org/abs/2406.03487 w/ @ElisaFerracane @zacharylipton
📣 Today, we are announcing our $150M Series C! This is one of the largest funding rounds made to date in generative AI for healthcare. We are grateful to the luminary investors and iconic institutions who believe in us and our mission—to power deeper understanding in healthcare. This round was led by @lightspeedvp who will be joining our board. Other new and existing investors joining the round include co-lead @Redpoint, with support from @IVP, @sparkcapital, @usv, @BessemerVP, @WittingtonVC, Mass General Brigham Artificial Intelligence and Digital Innovation Fund (AIDIF), Kaiser Permanente Ventures, and CVS Health Ventures. With this new capital, we will continue to push boldly into fundamental research, developing bedrock foundation models that draw upon vast troves of multimodal healthcare data. Looking forward to this new wave of possibilities as we continue to fulfill our vision of improving the lives of patients and clinicians. Read more about our Series C here: abridge.com/press-release/…
We are kicking-off November with an Open Session on Multilingual Language Modeling. @LiangDavis will join us for our Thursdays with Science – Open Session. The session will take place on the 2nd of Nov., at 2pm (WEST). Register at lnkd.in/dNzvDchY and join us!
Attending the Machine Learning for Healthcare conference in New York this Friday and Saturday? Stop by our booth for a real-time demo and learn how we’re improving the care experience for clinicians and their patients with thoughtful AI. mlforhc.org
cbsnews.com/chicago/video/…): interview this AM on @cbschicago about ChatGPT and UT Austin's own @UTGoodSystems grand challenge on the design, development, and evaluation of responsible AI technologies. @UTAustin @UTiSchool @EngagingNews
