@Cnr_Isti @SIGIRConf These works have been supported by the @EfraProject Extreme Food Risk Analytics.

The accepted contributions span a range of topics, from neural and efficient retrieval and #ConversationalSearch to counterfactual user modeling and resource-efficient #AI.

🚀 Exciting news from the #HPCLab @Cnr_Isti ! We are proud to share that our researchers will present six papers at @SIGIRConf 2025, the flagship conference in #InformationRetrieval and Search Technologies, which will take place from July 13 to 17 in Padua, Italy.

Saving Energy Without Wasting Power: The Algorithm That Optimises AI Datacenters https://t.co/9DEsVBbfYp This work has been supported by the @EfraProject #SustainableAI #GreenComputing

Scaling sparse embeddings to 138 M vectors—in milliseconds! Discover the Evolution of Sparse Information Retrieval. https://t.co/AT4rmVt0ej @EfraProject @fmnardini #informationretrieval #LargeLanguageModels

Can Smaller Language Models Compete with ChatGPT? A New Study Has the Answer! https://t.co/ppq2gietp2 Work supported by the @EfraProject #ConversationalAI #LLMs #ChatGPT #ConversationalSearch #NLP #ArtificialIntelligence

Why dimensions matter in AI models. Read the article: 👉 https://t.co/YztRNnMu9i This work has been supported by @EfraProject #InformationRetrieval #InformationSystems #QueryRepresentation

How can AI rank docs effectively across distributed, biased datasets? Discover how collaborative Learning to Rank models overcome nonuniform data challenges, boosting search accuracy by up to 17.92%! 🚀 #AI #MachineLearning 👉 https://t.co/7Q4AkszXg5 Work supported by @EfraProject

The paper "Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations" was partially supported by @EfraProject - Horizon Europe RIA “Extreme Food Risk Analytics” . https://t.co/17OZ57M17I

Best Paper Runner-up award at @SIGIRConf for our paper "Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations". Congratulation to @fmnardini @snbruch @cosimorulli1 @rventurini_ 👉 https://t.co/17OZ57M17I #InformationRetrieval #SIGIR2024 @IstiCnr

📜DESIRE-ME: Domain-Enhanced Supervised Information Retrieval Using Mixture-of-Experts. A new publication by @raffaele_perego @ntonellotto Conference proceedings from @ecir2024 https://t.co/93hdNvG7lP This work is supported by @EfraProject #EFRA #InformationRetrieval #IR #ECIR

📜Towards Robust Expert Finding incommunity questionn Answering Platforms. A new publication by Maddalena Amendola, @andrepassarella @raffaele_perego. Conf proceedings @ecir2024 https://t.co/tAQ0ZIJFua This work is supported by @EfraProject #EFRA #InformationRetrieval #IR #ECIR

📜Efficient Multi-vector Dense Retrieval with Bit Vectors. A new publication by @fmnardini @cosimorulli1 @rventurini_ . Conference proceedings from @ecir2024 This work is supported by @EfraProject #EFRA #InformationRetrieval #IR #ECIR

Rewriting Conversational Utterances with Instructed Large Language Models. An article by @GuidoRocchietti on Medium 👉 https://t.co/Mu6gDsjnjO This work is supported by @EfraProject #conversationalSearch #InformationRetrieval #EFRA @fmnardini @CriMuntean

Expanding Conversational Search: Commonsense Injection for Query Expansion. Read the article on @Medium 👉 https://t.co/zucA655kFE A work supported by @EfraProject #conversationalSearch #InformationRetrieval #EFRA @GuidoRocchietti @fmnardini @CriMuntean

Today, Andrew Yates @andrewyates from the University of Amsterdam will give an in-person seminar at ISTI-CNR (@isticnr) entitled "An encoder-centric view of neural retrieval". Thanks @andrewyates!

Enhancing Conversational Search with Large Language Models. An article by @GuidoRocchietti @fmnardini @CriMuntean on @ercim_news Read the article👇 https://t.co/Tont3nsBk8 #EFRA @EfraProject #HorizonEurope #ResearchImpactEU #AI #foodsafety #data #datamining #research

Our paper " DESIRE-ME: Domain-Enhanced Supervised Information REtrieval using Mixture-of-Experts" has been accepted at @ecir2024 in the ECIR 2024 findings. This work has been supported by @EfraProject Authors: Pranav Kasela, Gabriella Pasi, @raffaele_perego @ntonellotto

Our paper " Towards Transparent and Robust Expert Finding in Community Question Answering Platforms" has been accepted at @ecir2024 in the IR4Good track. This work has been supported by @EfraProject @maddalena0112 @andrepassarella @raffaele_perego #informationretrieval

Our long paper " Efficient Multi-Vector Dense Retrieval with Bit Vectors" has been accepted at @ecir2024 This work has been supported by @EfraProject @fmnardini @cosimorulli1 @rventurini_ #informationretrieval