Dual Encoder

method ID: dualencoder

Related Papers

Large-Scale Representation Learning from Visually Grounded Untranscribed Speech

Authors: nan

Publication: TIPSTER (2019)

DOI: nan

AbstractSystems that can associate images with their spoken audio captions are an important step towards visually grounded language learning. We describe a scalable method to automatically generate diverse audio for …...

41740

Learning Dense Representations for Entity Retrieval

Authors: nan

Publication: TIPSTER (2019)

DOI: nan

AbstractWe show that it is feasible to perform entity linking by training a dual encoder (two-tower) model that encodes mentions and entities in the same dense vector space, where candidate …...

41700

Entity Linking in 100 Languages

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractWe propose a new formulation for multilingual entity linking, where language-specific mentions resolve to a language-agnostic Knowledge Base. We train a dual encoder in this new setting, building on prior …...

29820

Cross-lingual Sentence Embedding using Multi-Task Learning

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractMultilingual sentence embeddings capture rich semantic information not only for measuring similarity between texts but also for catering to a broad range of downstream cross-lingual NLP tasks. State-of-the-art multilingual sentence …...

30989

Multi-Vector Attention Models for Deep Re-ranking

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Publication: TIPSTER (2021)

DOI: nan

AbstractLarge-scale document retrieval systems often utilize two styles of neural network models which live at two different ends of the joint computation vs. accuracy spectrum. The first style is dual …...

31660

MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractEntity retrieval, which aims at disambiguating mentions to canonical entities from massive KBs, is essential for many tasks in natural language processing. Recent progress in entity retrieval shows that the …...

31895

RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractIn open-domain question answering, dense passage retrieval has become a new paradigm to retrieve relevant passages for finding answers. Typically, the dual-encoder architecture is adopted to learn dense representations of …...

21284

Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractAspect-based sentiment analysis (ABSA) task consists of three typical subtasks: aspect term extraction, opinion term extraction, and sentiment polarity classification. These three subtasks are usually performed jointly to save resources …...

31795

Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractEfficient k-nearest neighbor search is a fundamental task, foundational for many problems in NLP. When the similarity is measured by dot-product between dual-encoder vectors or L2-distance, there already exist many …...

31400

IIT Bombay’s WMT22 Automatic Post-Editing Shared Task Submission

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractThis paper describes IIT Bombay’s submission to the WMT22 Automatic Post-Editing (APE) shared task for the English-Marathi (En-Mr) language pair. We follow the curriculum training strategy to train our APE …...

27486

Leaner and Faster: Two-Stage Model Compression for Lightweight Text-Image Retrieval

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Publication: TIPSTER (2022)

DOI: nan

AbstractCurrent text-image approaches (e.g., CLIP) typically adopt dual-encoder architecture using pre-trained vision-language representation. However, these models still pose non-trivial memory requirements and substantial incremental indexing time, which makes them less …...

21109

HiTIN: Hierarchy-aware Tree Isomorphism Network for Hierarchical Text Classification

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractHierarchical text classification (HTC) is a challenging subtask of multi-label classification as the labels form a complex hierarchical structure. Existing dual-encoder methods in HTC achieve weak performance gains with huge …...

38423