


TILOS Seminar: Unlearnable Facts Cause Hallucinations in Pretrained Language Models
HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United StatesAdam Tauman Kalai, OpenAI Abstract: Pretrained language models (LMs) tend to preserve many qualities present in their training data, such as grammaticality, formatting, and politeness. However, for specific types of factuality, even LMs pretrained on factually correct statements tend to produce falsehoods at high rates. We explain these “hallucinations” by drawing a connection to binary […]

TILOS-SDSU Seminar: Challenging Estimation Problems in Vehicle Autonomy
San Diego State University 5500 Campanile Dr, San Diego, United StatesRajesh Rajamani, University of Minnesota Abstract: This talk presents some interesting problems in estimation related to vehicle autonomy. First, a teleoperation application in which a remote operator can intervene to control an autonomous vehicle is considered. Fundamental challenges here include the need to design an effective teleoperation station, bandwidth and time-criticality constraints in wireless communication, […]

TILOS Tutorial on AI Alignment
HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States
TILOS Seminar: Synthetic Tasks as Testbeds for Attributing Model Behavior
HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United StatesSurbhi Goel, University of Pennsylvania Abstract: Understanding how different components of the machine learning pipeline—spanning data composition, architectural choices, and optimization dynamics—shape model behavior remains a fundamental challenge. In this talk, I will argue that synthetic tasks, which enable precise control over data distribution and task complexity, serve as powerful testbeds for analyzing and attributing […]

TILOS-Cisco AI + Security Workshop
HDSI 123 3234 Matthews Ln, La Jolla, CA, United States
TILOS Seminar: Single location regression and attention-based models
HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United StatesClaire Boyer, Université Paris-Saclay Abstract: Attention-based models, such as Transformer, excel across various tasks but lack a comprehensive theoretical understanding, especially regarding token-wise sparsity and internal linear representations. To address this gap, we introduce the single-location regression task, where only one token in a sequence determines the output, and its position is a latent random […]

TILOS Seminar: Foundational Methods for Foundation Models for Scientific Machine Learning
HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United StatesMichael W. Mahoney, ICSI, LBNL, and Department of Statistics, UC Berkeley Abstract: The remarkable successes of ChatGPT in natural language processing (NLP) and related developments in computer vision (CV) motivate the question of what foundation models would look like and what new advances they would enable, when built on the rich, diverse, multimodal data that […]