In our quest to understand the current wave of activity in Natural Language Processing (NLP), and in particular Large Language Models (LLM), we are happy to launch our second season of talks.
We invite the first authors from some seminal LLM papers to talk through their paper, explore any common misconceptions they’ve encountered, and lead a discussion on how things have changed since the paper came out.
ALTERNATE TUESDAYS STARTING MARCH 5, 12:00-1:00 PM EST on Zoom
RSVP on EventBrite: https://www.eventbrite.ca/e/llm-reading-group-march-5-19-april-2-16-30-may-14-tickets-851921368747?aff=oddtdtcreator
- March 5 The Linear Representation Hypothesis and the Geometry of Large Language Models: https://arxiv.org/abs/2311.03658 with Kiho Park (Google Brain
- March 19 Who Are the Publics Engaging in AI? https://journals.sagepub.com/doi/10.1177/09636625231219853 with Renee Sieber (McGill University)
- April 2 Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models https://arxiv.org/abs/2401.01301 with Matt Dahl (Yale), Verun Magesh; Mirac Suzgun (Stanford)
- April 16 Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning https://arxiv.org/abs/2402.06619 with Marzieh Fadaee, Ahmet Ustun (Cohere For AI)
- April 30 How Well Can LLMs Negotiate? Negotiation Arena Platform and Analysis https://arxiv.org/abs/2402.05863 with Federico Bianchi (Stanford)
- May 14 Detecting LLM Generated Text in Computing Education: A Comparative Study for ChatGPT Cases: https://arxiv.org/abs/2307.07411 with Michael Liut (University of Toronto)
Join us on Discord for recordings of past sessions, discussions and future session ideas: https://discord.gg/a8auUyKAgB
In partnership with the Human Feedback Foundation: https://humanfeedback.io/