May 21, 2022 · We compare our model - NS3 (Neuro-Symbolic Semantic Search) - to a number of baselines, including state-of-the-art semantic code retrieval methods.

The semantic layout is used to break down the final reasoning decision into a series of lower-level decisions. We use a Neural. Module Network architecture to ...

We identify the entities and the actions in the query and how they relate to each other. We do that by creating the semantic parse of the query. • entities are ...

Apr 3, 2024 · We compare our model - NS3 (Neuro-Symbolic Semantic Search) - to a number of baselines, including state-of-the-art semantic code retrieval ...

Code for NS3: Neuro-Symbolic Semantic Code Search. Contribute to ShushanArakelyan/modular_code_search development by creating an account on GitHub.

Oct 31, 2022 · The paper introduces a novel method for semantic code search using neural module networks. The layout of the network is produced from a semantic ...

This work proposes supplementing the query sentence with a layout of its semantic structure, used to break down the final reasoning decision into a series ...

Code search aims to retrieve the most semantically relevant code snippet for a given natural language query. Recently, large-scale code pre-trained models such ...

Nov 7, 2022 · The semantic layout is used to break down the final reasoning decision into a series of lower-level decisions. We use a Neural. Module Network ...

In this paper, we define a neuro-symbolic approach to address the task of finding semantically similar clones for the codes of the legacy ...