Cem Anil

Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data

2024 · arXiv (Cornell University)

One way to address safety risks from large language models (LLMs) is to censor dangerous knowledge from their training data. While this removes the explicit information, implicit information can remain scattered across various training documents. …

Solving Quantitative Reasoning Problems with Language Models

2022 · arXiv (Cornell University)

Language models have achieved remarkable performance on a wide range of tasks that require natural language understanding. Nevertheless, state-of-the-art models have generally struggled with tasks that require quantitative reasoning, such as solving mathematics, science, and …