Matthias Hagen Profile
Matthias Hagen

@matthias_hagen

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Professor of "Databases and Information Systems", Friedrich-Schiller-Universität Jena

Jena, Germany
Joined November 2010
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@matthias_hagen
Matthias Hagen
1 day
RT @webis_de: Honored to win the ICTIR Best Paper Honorable Mention Award for "Axioms for Retrieval-Augmented Generation"!.Our new axioms a….
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@matthias_hagen
Matthias Hagen
3 days
RT @webis_de: Happy to share that our paper "The Viability of Crowdsourcing for RAG Evaluation" received the Best Paper Honourable Mention….
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@matthias_hagen
Matthias Hagen
3 days
RT @fschlatt1: Want to know how to make bi-encoders more than 3x faster with a new backbone encoder model? Check out our talk on the Token-….
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@matthias_hagen
Matthias Hagen
22 days
RT @maik_froebe: Do not forget to participate in the #TREC2025 Tip-of-the-Tongue (ToT) Track :). The corpus and baselines (with run files)….
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@matthias_hagen
Matthias Hagen
3 months
RT @fschlatt1: What an honor to receive both the best short paper award and the best paper honourable mention award at #ECIR2025. Thank you….
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@matthias_hagen
Matthias Hagen
3 months
RT @webis_de: 🧵 4/4 Credit and thanks to the author team.@LukasGienapp, Tim Hagen, @maik_froebe,.@matthias_hagen, @bennostein, .@martinpott….
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@matthias_hagen
Matthias Hagen
3 months
RT @webis_de: 🧵 3/4 This fundamentally challenges previous assumptions about RAG evaluation and system design. But we also show how crowdso….
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@matthias_hagen
Matthias Hagen
3 months
RT @webis_de: 🧵2/4 Key findings: 1️⃣ Humans write best? No! LLM responses are rated better than human. 2️⃣ Essay answers? No! Bullet lists….
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@matthias_hagen
Matthias Hagen
3 months
RT @webis_de: 📢 Our paper "The Viability of Crowdsourcing for RAG Evaluation" has been accepted to #SIGIR2025 ! We compared how good humans….
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@matthias_hagen
Matthias Hagen
3 months
RT @fschlatt1: Next up at #ECIR2025, @maik_froebe presenting his fantastic work on corpus sub sampling and how to more efficiently evaluate….
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@matthias_hagen
Matthias Hagen
8 months
RT @fschlatt1: Happy to share our framework for fine-tuning and running neural ranking models, Lightning IR, was accepted as a demo at #WSD….
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@matthias_hagen
Matthias Hagen
8 months
RT @_reachsumit: Lightning IR: Straightforward Fine-tuning and Inference of Transformer-based Language Models for Information Retrieval. In….
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@matthias_hagen
Matthias Hagen
10 months
RT @H1iReimer: Follow-up on our #BIOASQ2024 submission: We actually submitted the best approach for some of the tasks 👍.Looking forward to….
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@matthias_hagen
Matthias Hagen
10 months
RT @H1iReimer: @maik_froebe Great talk on the Team @OpenWebSearchEU's submission to the QuantumCLEF shared task on how to exploit #QuantumC….
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@matthias_hagen
Matthias Hagen
10 months
RT @H1iReimer: @albondarenko2 Thanks!.You can find out paper and code online:.#CLEF2024.
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@matthias_hagen
Matthias Hagen
10 months
RT @albondarenko2: Great presentation about RAG in biomedical domain @H1iReimer .#CLEF2024 #BIOASQ2024
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@matthias_hagen
Matthias Hagen
11 months
RT @albondarenko2: @H1iReimer presented our short paper at #ArgMining2024 at #ACL2024 today. We proposed to add "semantics" to lexical re….
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@matthias_hagen
Matthias Hagen
1 year
RT @webis_de: Goodbye Washington! We had a fantastic week with interesting talks, discussions, and new ideas at #SIGIR24 #SIGIR2024. We hop….
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@matthias_hagen
Matthias Hagen
1 year
RT @hscells: Check out the paper:
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