Natural Language Queries

105 papers with code • 1 benchmarks • 2 datasets

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Most implemented papers

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

github/CodeSearchNet 20 Sep 2019

To enable evaluation of progress on code search, we are releasing the CodeSearchNet Corpus and are presenting the CodeSearchNet Challenge, which consists of 99 natural language queries with about 4k expert relevance annotations of likely results from CodeSearchNet Corpus.

TALL: Temporal Activity Localization via Language Query

jiyanggao/TALL ICCV 2017

For evaluation, we adopt TaCoS dataset, and build a new dataset for this task on top of Charades by adding sentence temporal annotations, called Charades-STA.

QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries

jayleicn/moment_detr 20 Jul 2021

Each video in the dataset is annotated with: (1) a human-written free-form NL query, (2) relevant moments in the video w. r. t.

Use What You Have: Video Retrieval Using Representations From Collaborative Experts

albanie/collaborative-experts 31 Jul 2019

The rapid growth of video on the internet has made searching for video content using natural language queries a significant challenge.

How Much Knowledge Can You Pack Into the Parameters of a Language Model?

google-research/google-research EMNLP 2020

It has recently been observed that neural language models trained on unstructured text can implicitly store and retrieve knowledge using natural language queries.

V3CTRON | Data Retrieval & Access System For Flexible Semantic Search & Retrieval Of Proprietary Document Collections Using Natural Language Queries.

serp-ai/V3CTRON-vector-database-embedding-neural-search-retrieval-chatgpt-plugin Social Science Research Network (SSRN) 2023

V3CTRON is an open source vector database that allows users to upload text based documents & document collections, which are automatically embedded for super-accurate semantic search & retrieval using natural language queries.

Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge

nicholaslocascio/deep-regex EMNLP 2016

This paper explores the task of translating natural language queries into regular expressions which embody their meaning.

Learning a Natural Language Interface with Neural Programmer

tensorflow/models 28 Nov 2016

The main experimental result in this paper is that a single Neural Programmer model achieves 34. 2% accuracy using only 10, 000 examples with weak supervision.

Function Assistant: A Tool for NL Querying of APIs

yakazimir/Code-Datasets EMNLP 2017

For a given text query and background API, the tool finds candidate functions by performing a translation from the text to known representations in the API using the semantic parsing approach of Richardson and Kuhn (2017).

Localizing Moments in Video with Natural Language

lisaanne/localizingmoments ICCV 2017

A key obstacle to training our MCN model is that current video datasets do not include pairs of localized video segments and referring expressions, or text descriptions which uniquely identify a corresponding moment.