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10 papers · 1 filter
SQuAI: Scientific Question-Answering with Multi-Agent Retrieval-Augmented Generation
Ines Besrour, Jingbo He, Tobias Schreieder +1
We present SQuAI (https://squai.scads.ai/), a scalable and trustworthy multi-agent retrieval-augmented generation (RAG) framework for scientific question answering (QA) with large…
Simplified Longitudinal Retrieval Experiments: A Case Study on Query Expansion and Document Boosting
Jüri Keller, Maik Fröbe, Gijs Hendriksen +3
The longitudinal evaluation of retrieval systems aims to capture how information needs and documents evolve over time. However, classical Cranfield-style retrieval evaluations only…
The Viability of Crowdsourcing for RAG Evaluation
Lukas Gienapp, Tim Hagen, Maik Fröbe +4
How good are humans at writing and judging responses in retrieval-augmented generation (RAG) scenarios? To answer this question, we investigate the efficacy of crowdsourcing for RA…
Systematic Evaluation of Neural Retrieval Models on the Touché 2020 Argument Retrieval Subset of BEIR
Nandan Thakur, Luiz Bonifacio, Maik Fröbe +5
The zero-shot effectiveness of neural retrieval models is often evaluated on the BEIR benchmark -- a combination of different IR evaluation datasets. Interestingly, previous studie…
Learning Effective Representations for Retrieval Using Self-Distillation with Adaptive Relevance Margins
Lukas Gienapp, Niklas Deckers, Martin Potthast +1
Representation-based retrieval models, so-called bi-encoders, estimate the relevance of a document to a query by calculating the similarity of their respective embeddings. Current…
Detecting Generated Native Ads in Conversational Search
Sebastian Schmidt, Ines Zelch, Janek Bevendorff +3
Conversational search engines such as YouChat and Microsoft Copilot use large language models (LLMs) to generate responses to queries. It is only a small step to also let the same…