44 citations · 167 across the 30 of their papers we have counts for
9 papers · 1 filter
2D Matryoshka Training for Information Retrieval
Shuai Wang, Shengyao Zhuang, Bevan Koopman +1
2D Matryoshka Training is an advanced embedding representation training approach designed to train an encoder model simultaneously across various layer-dimension setups. This metho…
Starbucks-v2: Improved Training for 2D Matryoshka Embeddings
Shengyao Zhuang, Shuai Wang, Fabio Zheng +2
2D Matryoshka training enables a single embedding model to generate sub-network representations across different layers and embedding dimensions, offering adaptability to diverse c…
Context Embeddings for Efficient Answer Generation in RAG
David Rau, Shuai Wang, Hervé Déjean +1
Retrieval-Augmented Generation (RAG) allows overcoming the limited knowledge of LLMs by extending the input with external information. As a consequence, the contextual inputs to th…
BERGEN: A Benchmarking Library for Retrieval-Augmented Generation
David Rau, Hervé Déjean, Nadezhda Chirkova +4
Retrieval-Augmented Generation allows to enhance Large Language Models with external knowledge. In response to the recent popularity of generative LLMs, many RAG approaches have be…
An Investigation of Prompt Variations for Zero-shot LLM-based Rankers
Shuoqi Sun, Shengyao Zhuang, Shuai Wang +1
We provide a systematic understanding of the impact of specific components and wordings used in prompts on the effectiveness of rankers based on zero-shot Large Language Models (LL…
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation
Shuai Wang, Ekaterina Khramtsova, Shengyao Zhuang +1
Federated search systems aggregate results from multiple search engines, selecting appropriate sources to enhance result quality and align with user intent. With the increasing upt…
Large Language Models for Stemming: Promises, Pitfalls and Failures
Shuai Wang, Shengyao Zhuang, Guido Zuccon
Text stemming is a natural language processing technique that is used to reduce words to their base form, also known as the root form. The use of stemming in IR has been shown to o…
Zero-shot Generative Large Language Models for Systematic Review Screening Automation
Shuai Wang, Harrisen Scells, Shengyao Zhuang +3
Systematic reviews are crucial for evidence-based medicine as they comprehensively analyse published research findings on specific questions. Conducting such reviews is often resou…
ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search
Shuai Wang, Shengyao Zhuang, Bevan Koopman +1
Federated search, which involves integrating results from multiple independent search engines, will become increasingly pivotal in the context of Retrieval-Augmented Generation pip…