I3 retriever: incorporating implicit interaction in pre-trained language models for passage retrieval
Passage retrieval is a fundamental task in many information systems, such as web search
and question answering, where both efficiency and effectiveness are critical concerns. In …
and question answering, where both efficiency and effectiveness are critical concerns. In …
CAME: Competitively Learning a Mixture-of-Experts Model for First-stage Retrieval
The first-stage retrieval aims to retrieve a subset of candidate documents from a huge
collection both effectively and efficiently. Since various matching patterns can exist between …
collection both effectively and efficiently. Since various matching patterns can exist between …
Retrieval-based Disentangled Representation Learning with Natural Language Supervision
Disentangled representation learning remains challenging as the underlying factors of
variation in the data do not naturally exist. The inherent complexity of real-world data makes …
variation in the data do not naturally exist. The inherent complexity of real-world data makes …
L2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible Representations
First-stage retrieval is a critical task that aims to retrieve relevant document candidates from
a large-scale collection. While existing retrieval models have achieved impressive …
a large-scale collection. While existing retrieval models have achieved impressive …
Pre-training with Large Language Model-based Document Expansion for Dense Passage Retrieval
In this paper, we systematically study the potential of pre-training with Large Language
Model (LLM)-based document expansion for dense passage retrieval. Concretely, we …
Model (LLM)-based document expansion for dense passage retrieval. Concretely, we …
Query-as-context Pre-training for Dense Passage Retrieval
Recently, methods have been developed to improve the performance of dense passage
retrieval by using context-supervised pre-training. These methods simply consider two …
retrieval by using context-supervised pre-training. These methods simply consider two …
Drop your Decoder: Pre-training with Bag-of-Word Prediction for Dense Passage Retrieval.
Masked auto-encoder pre-training has emerged as a prevalent technique for initializing and
enhancing dense retrieval systems. It generally utilizes additional Transformer decoder …
enhancing dense retrieval systems. It generally utilizes additional Transformer decoder …
Improving News Recommendation via Bottlenecked Multi-task Pre-training
X Xiao, Q Li, S Liu, K Zhou - Proceedings of the 46th International ACM …, 2023 - dl.acm.org
Recent years have witnessed the boom of deep neural networks in online news
recommendation service. As news articles mainly consist of textual content, pre-trained …
recommendation service. As news articles mainly consist of textual content, pre-trained …
Query-as-context Pre-training for Dense Passage Retrieval
Recently, methods have been developed to improve the performance of dense passage
retrieval by using context-supervised pre-training. These methods simply consider two …
retrieval by using context-supervised pre-training. These methods simply consider two …
Cot-mae v2: contextual masked auto-encoder with multi-view modeling for passage retrieval
Growing techniques have been emerging to improve the performance of passage retrieval.
As an effective representation bottleneck pretraining technique, the contextual masked auto …
As an effective representation bottleneck pretraining technique, the contextual masked auto …