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Great news from #SIGIR2025 — our (/w Craig Macdonald and Nicola Tonellotto) full paper “Efficient Recommendation with Millions of Items by Dynamic Pruning of Sub-Item Embeddings” has been accepted. Nice timing too: all co-authors are now at ECIR, so we get to celebrate together.

Watching Jack McKechnie present our work on context selection for LLM evaluation w/ graham mcdonald #ecir2025

Now Fangzheng Tian is presenting our work on relevance propagated from retriever to generator in RAG w/ Debasis Ganguly Glasgow IR Group #ecir2025

Now Ariane Müller is giving a talk about analysing semantic matching in ColBERT. Very interesting stuff, go check out the poster later on! ECIR2025 Glasgow IR Group UofG Computing Science #ECIR2025

Great work and presentation by UofG Computing Science MSc student Ariane Müller about analysing semantic matching in ColBERT at the Findings session of ECIR2025. You can still check out her work at the #ecir2025 poster session later on!

Congratulations to Manish Chandra Debasis Ganguly and Iadh Ounis for being awarded the Best Paper Award at #ECIR2025 for their work entitled “One size doesn’t fit all: Predicting the number of examples for in-context learning”. The paper will be presented Wednesday morning in Lucca.

Manish Chandra is presenting the #ecir2025 best paper award paper: one size doesn’t fit all: predicting the number of examples for in-context learning w/ Debasis Ganguly Iadh Ounis Glasgow IR Group cc/UofG Computing Science

In the #ecir2025 QPP+ workshop, Fangzheng Tian is presenting our work on revisitingquery variants for QPP w/ Debasis Ganguly cc/ Glasgow IR Group

Keynote presentation by Debasis Ganguly in the QPP++ workshop at #ecir2025 Cc/ Glasgow IR Group

. Sean MacAvaney and I just talked about caching and precomputation in PyTerrier declarative experiments in the #ecir2025 OpenWebSearch workshop cc/ Glasgow IR Group

.Andreas Chari talking about fine tuning dense retrieval models for low resource languages #ecir2025. Work with Sean MacAvaney and Iadh Ounis cc/ Glasgow IR Group

When will Google Scholar deploy some gen AI capabilities? Would really enhance finding citations that illustrate a point you want to make in a paper...

As Harry Scells et al say: ♻️ Reduce, Reuse, Recycle! It's never been easier to share indexes (Terrier, Anserini, Pisa, Dense, etc.) using HuggingFace, Zenodo, etc. 🤓

.@sharepoint any update on when we can copy from a PDF? same on Microsoft Teams... answers.microsoft.com/en-us/msteams/…

🎉 Glad to share that our paper "KiRAG: Knowledge-Driven Iterative Retriever for Enhancing Retrieval-Augmented Generation" (w/ Zaiqiao Meng and Craig Macdonald) has been accepted at #ACL2025 as a main conference paper!

I'm delighted to announce that I'm joining hashtag @Amazon Edinburgh as a part-time Visiting Scholar, working on recommendations

Delighted that Aleksandr V. Petrov passed his 🎓 PhD defense this morning, without corrections. Thanks to Pablo Castells and Nicolas Pugeault for their thorough examination of the thesis, and Mireilla Bikanga Ada for convening the defense!

❓Which retrieval library should you use for RAG? Which agent library? Where do you get datasets? We made PyTerrier RAG to stop your headaches! Led by Craig Macdonald /w (Jinyuan Fang , me and Zaiqiao Meng )! 🧵 ⬇️