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07/24/2023
RRAML: Reinforced Retrieval Augmented Machine Learning
The emergence of large language models (LLMs) has revolutionized machine...
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05/30/2023
A Federated Channel Modeling System using Generative Neural Networks
The paper proposes a data-driven approach to air-to-ground channel estim...
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05/18/2023
Integrating Item Relevance in Training Loss for Sequential Recommender Systems
Sequential Recommender Systems (SRSs) are a popular type of recommender ...
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04/25/2023
A Static Pruning Study on Sparse Neural Retrievers
Sparse neural retrievers, such as DeepImpact, uniCOIL and SPLADE, have b...
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11/25/2022
Caching Historical Embeddings in Conversational Search
Rapid response, namely low latency, is fundamental in search application...
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08/18/2022
Adaptive Re-Ranking with a Corpus Graph
Search systems often employ a re-ranking pipeline, wherein documents (or...
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07/27/2022
Lecture Notes on Neural Information Retrieval
These lecture notes focus on the recent advancements in neural informati...
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04/24/2022
Faster Learned Sparse Retrieval with Guided Traversal
Neural information retrieval architectures based on transformers such as...
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08/25/2021
On Approximate Nearest Neighbour Selection for Multi-Stage Dense Retrieval
Dense retrieval, which describes the use of contextualised language mode...
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08/23/2021
Query Embedding Pruning for Dense Retrieval
Recent advances in dense retrieval techniques have offered the promise o...
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08/13/2021
On Single and Multiple Representations in Dense Passage Retrieval
The advent of contextualised language models has brought gains in search...
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06/21/2021
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval
Pseudo-relevance feedback mechanisms, from Rocchio to the relevance mode...
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04/24/2021
Learning Passage Impacts for Inverted Indexes
Neural information retrieval systems typically use a cascading pipeline,...
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07/28/2020
Declarative Experimentation in Information Retrieval using PyTerrier
The advent of deep machine learning platforms such as Tensorflow and Pyt...
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04/29/2020
Training Curricula for Open Domain Answer Re-Ranking
In precision-oriented tasks like answer ranking, it is more important to...
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04/29/2020
Efficient Document Re-Ranking for Transformers by Precomputing Term Representations
Deep pretrained transformer networks are effective at various ranking ta...
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04/29/2020
Expansion via Prediction of Importance with Contextualization
The identification of relevance with little textual context is a primary...
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01/09/2020