Location: 2055 Hoover Hall, Iowa State University (Zoom link is also provided for the audience external to ISU)
Title: From LLMs to LRMs: The Jagged Quest to Tease Planning and Reasoning from Humanity’s Digital Footprints
Abstract
Large Language Models, auto-regressively trained on the digital footprints of humanity, have shown impressive abilities in generating coherent text completions for a vast variety of prompts. While they excelled in producing completions in appropriate style, factuality and reasoning/planning abilities remained their Achilles heel. More recently a variety of approaches are being tried to improve the reasoning abilities and some are starting to show promise. These approaches leverage two broad and largely independent ideas: (i) test-time inference – which involves getting LLMs do more work than simply providing the most likely completion, including using them in generate and test approaches such as LLM-Modulo and (ii) post-training methods–which go beyond simple auto-regressive training on web corpora by collecting, filtering and training on derivational traces (popularly referred to as chains of thought), and modifying the base LLM with it using supervised finetuning or reinforcement learning methods. Their success notwithstanding, there are considerable misunderstandings about these methods–including whether they can provide correctness guarantees, whether they do adaptive computation and whether the intermediate tokens they generate can be viewed as reasoning traces in any meaningful sense. Drawing from our ongoing work, I will present a broad unifying perspective on these approaches and their promise and limitations.
Speaker Bio
Subbarao Kambhampati is a professor of computer science at Arizona State University. Kambhampati studies fundamental problems in planning and decision making, motivated in particular by the challenges of human-aware AI systems. He is a fellow of Association for the Advancement of Artificial Intelligence, American Association for the Advancement of Science, and Association for Computing machinery, and a recent recipient of the AAAI Patrick H. Winston Outstanding Educator award. He served as the president of the Association for the Advancement of Artificial Intelligence, a trustee of the International Joint Conference on Artificial Intelligence, the chair of AAAS Section T (Information, Communication and Computation), and a founding board member of Partnership on AI. Kambhampati’s research as well as his views on the progress and societal impacts of AI have been featured in multiple national and international media outlets. He can be followed on Twitter @rao2z.
