UofG IDA Section, Glasgow CS
@idaglasgow.bsky.social
Information, Data & Analysis Section of the School of Computing Science, University of Glasgow. 80+ researchers in IR, machine learning, vision & data systems. https://www.gla.ac.uk/schools/computing/research/researchsections/ida-section/
Reposted by UofG IDA Section, Glasgow CS
🎄 PyTerrier Advent 24/25: Removing low-quality docs can boost search quality and cut indexing costs. Our SIGIR’24 paper QT5 trains a T5 model to filter passages at indexing time—easy to integrate, and works with dense, PISA, or SPLADE indexes too.
December 24, 2025 at 9:23 AM
🎄 PyTerrier Advent 24/25: Removing low-quality docs can boost search quality and cut indexing costs. Our SIGIR’24 paper QT5 trains a T5 model to filter passages at indexing time—easy to integrate, and works with dense, PISA, or SPLADE indexes too.
Reposted by UofG IDA Section, Glasgow CS
🎄 PyTerrier Advent 22/25: A more complex pipeline—knowledge-graph–enhanced RAG from our EMNLP 2024 paper TRACE. We build a KG over retrieved docs, then use a transformer to reason over triples for better QA. This pipeline instantiation uses a cache (see 20th advent) on LLM-based KG extraction.
December 22, 2025 at 12:25 PM
🎄 PyTerrier Advent 22/25: A more complex pipeline—knowledge-graph–enhanced RAG from our EMNLP 2024 paper TRACE. We build a KG over retrieved docs, then use a transformer to reason over triples for better QA. This pipeline instantiation uses a cache (see 20th advent) on LLM-based KG extraction.
Reposted by UofG IDA Section, Glasgow CS
🎄 PyTerrier Advent 13/25: Doc2query expands docs with generated queries, but can hallucinate. Our ECIR’23 paper Doc2query-- (aka "minus minus") filters generated queries using a cross-encoder before indexing.
PyTerrier pipeline: generate→score→filter→index.
📄https://arxiv.org/pdf/2301.03266
PyTerrier pipeline: generate→score→filter→index.
📄https://arxiv.org/pdf/2301.03266
December 13, 2025 at 11:19 AM
🎄 PyTerrier Advent 13/25: Doc2query expands docs with generated queries, but can hallucinate. Our ECIR’23 paper Doc2query-- (aka "minus minus") filters generated queries using a cross-encoder before indexing.
PyTerrier pipeline: generate→score→filter→index.
📄https://arxiv.org/pdf/2301.03266
PyTerrier pipeline: generate→score→filter→index.
📄https://arxiv.org/pdf/2301.03266
Reposted by UofG IDA Section, Glasgow CS
🎄PyTerrier Advent 8/25: Beyond sparse! PyTerrier_dr adds dense indexing & retrieval. Instantiate an encoder model, compose with FlexIndex. Retrieval is identical. Support models include: ANCE, TCT-ColBERT, BGE, E5, or any SentenceTransformer model.
👉 github.com/terrierteam/...
👉 github.com/terrierteam/...
December 8, 2025 at 8:40 AM
🎄PyTerrier Advent 8/25: Beyond sparse! PyTerrier_dr adds dense indexing & retrieval. Instantiate an encoder model, compose with FlexIndex. Retrieval is identical. Support models include: ANCE, TCT-ColBERT, BGE, E5, or any SentenceTransformer model.
👉 github.com/terrierteam/...
👉 github.com/terrierteam/...