4 citations · 4 across the 4 of their papers we have counts for
6 papers
LeanSide: A Formally Verified Co-Reasoning System for Natural-language Proofs
Chenjun Guo, Manooshree Patel, Arnav Mehta +7
Large language models are increasingly used as collaborators on deductive-reasoning tasks, but their outputs can hallucinate or pull users away from intended reasoning. Formal proo…
A Fast Quantitative Analyzer for NetKAT
Thomas Lu, Qiancheng Fu, Kevin Batz +5
When designing a network, engineers must navigate trade-offs (e.g., one topology offers more aggregate bandwidth, another lower latency or better resilience) that demand reasoning…
LeanTutor: Towards a Verified AI Mathematical Proof Tutor
Manooshree Patel, Rayna Bhattacharyya, Thomas Lu +4
This paper considers the development of an AI-based provably-correct mathematical proof tutor. While Large Language Models (LLMs) allow seamless communication in natural language,…
Enhancing Fault-Tolerant Space Computing: Guidance Navigation and Control (GNC) and Landing Vision System (LVS) Implementations on Next-Gen Multi-Core Processors
Kyongsik Yun, David Bayard, Gerik Kubiak +5
Future planetary exploration missions demand high-performance, fault-tolerant computing to enable autonomous Guidance, Navigation, and Control (GNC) and Lander Vision System (LVS)…
LeanTutor: Towards a Verified AI Mathematical Proof Tutor
Manooshree Patel, Rayna Bhattacharyya, Thomas Lu +4
This paper considers the development of an AI-based provably-correct mathematical proof tutor. While Large Language Models (LLMs) allow seamless communication in natural language,…
Active Learning of Symbolic NetKAT Automata
Mark Moeller, Tiago Ferreira, Thomas Lu +2
NetKAT is a domain-specific programming language and logic that has been successfully used to specify and verify the behavior of packet-switched networks. This paper develops techn…