all AI news
Code Translation with Compiler Representations. (arXiv:2207.03578v2 [cs.PL] UPDATED)
July 14, 2022, 1:12 a.m. | Marc Szafraniec, Baptiste Roziere, Hugh Leather, Francois Charton, Patrick Labatut, Gabriel Synnaeve
cs.CL updates on arXiv.org arxiv.org
In this paper, we leverage low-level compiler intermediate representations
(IR) to improve code translation. Traditional transpilers rely on syntactic
information and handcrafted rules, which limits their applicability and
produces unnatural-looking code. Applying neural machine translation (NMT)
approaches to code has successfully broadened the set of programs on which one
can get a natural-looking translation. However, they treat the code as
sequences of text tokens, and still do not differentiate well enough between
similar pieces of code which have different semantics …
More from arxiv.org / cs.CL updates on arXiv.org
Benchmarking LLMs via Uncertainty Quantification
2 days, 7 hours ago |
arxiv.org
CARE: Extracting Experimental Findings From Clinical Literature
2 days, 7 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Field Sample Specialist (Air Sampling) - Eurofins Environment Testing – Pueblo, CO
@ Eurofins | Pueblo, CO, United States
Camera Perception Engineer
@ Meta | Sunnyvale, CA