activity
20192022
most citedText and Code Embeddings by Contrastive Pre-Training

152 citations · 204 across the 8 of their papers we have counts for

collaborators

9 papers

cs.LG202224 cited

Formal Mathematics Statement Curriculum Learning

Stanislas Polu, Jesse Michael Han, Kunhao Zheng +3

We explore the use of expert iteration in the context of language modeling applied to formal mathematics. We show that at same compute budget, expert iteration, by which we mean pr…

cs.CL2022152 cited

Text and Code Embeddings by Contrastive Pre-Training

Arvind Neelakantan, Tao Xu, Raul Puri +22

Text embeddings are useful features in many applications such as semantic search and computing text similarity. Previous work typically trains models customized for different use c…

cs.CL202110 cited

Unsupervised Neural Machine Translation with Generative Language Models Only

Jesse Michael Han, Igor Babuschkin, Harrison Edwards +8

We show how to derive state-of-the-art unsupervised neural machine translation systems from generatively pre-trained language models. Our method consists of three steps: few-shot a…

cs.DS2021

-Equivalence Relations and Associated Algorithms

Daniel Selsam, Jesse Michael Han

Lines and circles pose significant scalability challenges in synthetic geometry. A line with points implies collinearity atoms, or alternatively, when lines are…

math.LO202110 cited

A Formal Proof of the Independence of the Continuum Hypothesis

Jesse Michael Han, Floris van Doorn

We describe a formal proof of the independence of the continuum hypothesis () in the Lean theorem prover. We use Boolean-valued models to give forcing arguments for bo…

cs.AI20201 cited

Universal Policies for Software-Defined MDPs

Daniel Selsam, Jesse Michael Han, Leonardo de Moura +1

We introduce a new programming paradigm called oracle-guided decision programming in which a program specifies a Markov Decision Process (MDP) and the language provides a universal…