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Found 6 papers, 0 papers with code
Multi-stage Training with Improved Negative Contrast for Neural Passage Retrieval
In the context of neural passage retrieval, we study three promising techniques: synthetic data generation, negative sampling, and fusion.
Self-Supervised Learning for Pairwise Data Refinement
We evaluate our methods on de-noising parallel texts and training neural machine translation models.
Neural Passage Retrieval with Improved Negative Contrast
In this paper we explore the effects of negative sampling in dual encoder models used to retrieve passages for automatic question answering.
Multilingual Universal Sentence Encoder for Semantic Retrieval
We introduce two pre-trained retrieval focused multilingual sentence encoding models, respectively based on the Transformer and CNN model architectures.
Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax
On the UN document-level retrieval task, document embeddings achieve around 97% on P@1 for all experimented language pairs.
Effective Parallel Corpus Mining using Bilingual Sentence Embeddings
This paper presents an effective approach for parallel corpus mining using bilingual sentence embeddings.
