56 citations · 83 across the 7 of their papers we have counts for
7 papers
ExpeL: LLM Agents Are Experiential Learners
Andrew Zhao, Daniel Huang, Quentin Xu +3
The recent surge in research interest in applying large language models (LLMs) to decision-making tasks has flourished by leveraging the extensive world knowledge embedded in LLMs.…
Push: Concurrent Probabilistic Programming for Bayesian Deep Learning
Daniel Huang, Chris Camaño, Jonathan Tsegaye +1
We introduce a library called Push that takes a probabilistic programming approach to Bayesian deep learning (BDL). This library enables concurrent execution of BDL inference algor…
Elementary Logic in Linear Space
Daniel Huang
First-order logic is typically presented as the study of deduction in a setting with elementary quantification. In this paper, we take another vantage point and conceptualize first…
On Learning to Prove
Daniel Huang
In this paper, we consider the problem of learning a first-order theorem prover that uses a representation of beliefs in mathematical claims to construct proofs. The inspiration fo…
An Application of Computable Distributions to the Semantics of Probabilistic Programs
Daniel Huang, Greg Morrisett, Bas Spitters
In this chapter, we explore how (Type-2) computable distributions can be used to give both (algorithmic) sampling and distributional semantics to probabilistic programs with contin…
GamePad: A Learning Environment for Theorem Proving
Daniel Huang, Prafulla Dhariwal, Dawn Song +1
In this paper, we introduce a system called GamePad that can be used to explore the application of machine learning methods to theorem proving in the Coq proof assistant. Interacti…