Semantic Retrieval

12 papers with code • 1 benchmarks • 2 datasets

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Most implemented papers

Revealing the Importance of Semantic Retrieval for Machine Reading at Scale

easonnie/semanticRetrievalMRS IJCNLP 2019

In this work, we give general guidelines on system design for MRS by proposing a simple yet effective pipeline system with special consideration on hierarchical semantic retrieval at both paragraph and sentence level, and their potential effects on the downstream task.

Semantic query-by-example speech search using visual grounding

kamperh/flickr_semantic_qbe_eval 15 Apr 2019

A number of recent studies have started to investigate how speech systems can be trained on untranscribed speech by leveraging accompanying images at training time.

Contract Discovery: Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive Baselines

applicaai/contract-discovery Findings of the Association for Computational Linguistics 2020

We propose a new shared task of semantic retrieval from legal texts, in which a so-called contract discovery is to be performed, where legal clauses are extracted from documents, given a few examples of similar clauses from other legal acts.

Deep Unsupervised Image Hashing by Maximizing Bit Entropy

liyunqianggyn/Deep-Unsupervised-Image-Hashing 22 Dec 2020

This layer is shown to minimize a penalized term of the Wasserstein distance between the learned continuous image features and the optimal half-half bit distribution.

Semantic Models for the First-stage Retrieval: A Comprehensive Review

caiyinqiong/Semantic-Retrieval-Models 8 Mar 2021

We believe it is the right time to survey current status, learn from existing methods, and gain some insights for future development.

Evaluation of Audio-Visual Alignments in Visually Grounded Speech Models

khazarkhorrami/VGS_alignment 5 Jul 2021

We compare the alignment performance using our proposed evaluation metrics to the semantic retrieval task commonly used to evaluate VGS models.

Variational Transformer: A Framework Beyond the Trade-off between Accuracy and Diversity for Image Captioning

kaelsunkiller/vat 28 May 2022

In this work, we will show that the inferior standard of accuracy draws from human annotations (leave-one-out) are not appropriate for machine-generated captions.

PiC: A Phrase-in-Context Dataset for Phrase Understanding and Semantic Search

Phrase-in-Context/eval 19 Jul 2022

While contextualized word embeddings have been a de-facto standard, learning contextualized phrase embeddings is less explored and being hindered by the lack of a human-annotated benchmark that tests machine understanding of phrase semantics given a context sentence or paragraph (instead of phrases alone).

Training Effective Neural Sentence Encoders from Automatically Mined Paraphrases

sdadas/polish-sentence-evaluation 26 Jul 2022

Our sentence encoder can be trained in less than a day on a single graphics card, achieving high performance on a diverse set of sentence-level tasks.