Publication

Neural Code Search Evaluation Dataset

arXiv


Abstract

There has been an increase of interest in code search using natural language. Assessing the performance of such code search models can be difficult without a readily available evaluation suite. In this paper, we present an evaluation dataset of natural language query and code snippet pairs for future work. We also provide the results of two code search models ([6] and [1]) from recent work as a benchmark.

Related Publications

All Publications

CVPR - June 19, 2021

Robust Audio-Visual Instance Discrimination

Pedro Morgado, Ishan Misra, Nuno Vasconcelos

CVPR - June 19, 2021

Audio-Visual Instance Discrimination with Cross-Modal Agreement

Pedro Morgado, Nuno Vasconcelos, Ishan Misra

The Springer Series on Challenges in Machine Learning - December 12, 2019

The Second Conversational Intelligence Challenge (ConvAI2)

Emily Dinan, Varvara Logacheva, Valentin Malykh, Alexander Miller, Kurt Shuster, Jack Urbanek, Douwe Kiela, Arthur Szlam, Iulian Serban, Ryan Lowe, Shrimai Prabhumoye, Alan W. Black, Alexander Rudnicky, Jason Williams, Joelle Pineau, Jason Weston

ACM SIGIR - July 11, 2021

From Producer Success to Retention: a New Role of Search and Recommendation Systems on Marketplaces

Viet Ha-Thuc, Matthew Wood, Yunli Liu, Jagadeesan Sundaresan

To help personalize content, tailor and measure ads, and provide a safer experience, we use cookies. By clicking or navigating the site, you agree to allow our collection of information on and off Facebook through cookies. Learn more, including about available controls: Cookies Policy