Natural Language Queries
95 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Natural Language Queries
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Libraries
Use these libraries to find Natural Language Queries models and implementations
Ego4D
YouwikiHow
Most implemented papers
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
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
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.
Use What You Have: Video Retrieval Using Representations From Collaborative Experts
albanie/collaborative-experts
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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
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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.
QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries
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.
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
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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
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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
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
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
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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.
