📢The proceedings of the Italian Information Retrieval Workshop 2025 are now online.
Read and share the papers from #IIR2025 available here: https://t.co/MXQm76PhvW
Thanks to all authors, reviewers, and the editors for making this volume possible.
Tick-tock turned back! ⏰
You’ve got until July 4, 2025 to send your IR work to the Italian Information Retrieval Workshop 2025.
📅 Sept 3–5 • Univ. of Cagliari
✅ Free entry (just register)
Don’t let this encore slip, hit that CFP link now! 🔗 https://t.co/RR1alZIyKq
#IIR2025
⏳ Only three days to go! Submit to the Italian Information Retrieval Workshop 2025 (#IIR2025): “Human-Centric and Generative AI for Information Access” 🚀
🗓 CFP deadline: June 26, 2025 (11:59 pm AoE)
📍 Univ. of Cagliari, Sept 3–5, 2025
🔗 https://t.co/F113BMOKzo
So, where were we? 🤔
With the deadlines for #full and #short papers left behind, #UMAP2025 has still amazing calls to offer:
👩🏭 Industry (March 2)
👩🎓 DC* (March 7)
👩🏫 LBR & Demos (April 9)
*Hey, students, see the grants and support opportunities: https://t.co/E7snM68rfA
Some great news we want to share 🤩🤩 We’re happy to announce that the proceedings for the #IRonGraphs workshop, co-located with #ECIR2024@ecir2024, are officially out. Check them out at: https://t.co/nSRP6tMCB8. Thank you to all the authors for their amazing contributions 🚀🎉
Recently, #diffusion models in CV have been shown to produce possibly #biased images, eventually leading to #unfairness.
Thus, a natural question arises: "Does this also occur in #recommendation?" Maybe yes 🫢
Take a look at our pre-print 👇👇
https://t.co/l09T3Ev7mb
We are thrilled to announce the two **AMAZING** keynotes at #IRonGraphs WS 🚀
⭐️@Fra_Fabbri (@Spotify, Spain): Graph Foundation Model for Personalization
⭐️@RuihongQiu (@UQSchoolEECS, Australia): Graph Learning Methods in Session-based Recommendations and Legal Case Retrieval
📢Our paper "Robustness in Fairness against Edge-level Perturbations in GNN-based Recommendation" accepted at #ECIR2024 is out https://t.co/3uS0bq4jIZ!💪🏿Stay tuned for more developments on this topic!
w\ @ludovicoboratto, @Fra_Fabbri, G. Fenu, @mirkomarras#recsys#robust#fair
In our paper, we study the impact of edge-level perturbations on the robustness of GNN-based recommender systems. Grounded in an attack-like perspective, we delineate the unfair consequences of graph perturbations on consumer (CP, CS) and provider fairness (PE, PV) definitions.
Happy to share that the collaboration w/ @ludovicoboratto, @Fra_Fabbri, G. Fenu, @mirkomarras resulted in our paper "Robustness in Fairness against Edge-level Perturbations in GNN-based Recommendation" being accepted as a findings paper at @ecir2024.
📃Preprint soon available!!
In "Robustness in Fairness against Edge-level
Perturbations in GNN-based Recommendation", w/ @Fra_Fabbri, G. Fenu, @mirkomarras, @jackmedda, we study the robustness of graph-based recommender systems concerning fairness, when exposed to attacks based on edge-level perturbations.
Would you like to be a reviewer at #IRonGraphs, the 1st International WS on #Graph-Based Approaches in #IR? We are recruiting new reviewers 💪📝If you are interested, fill in this form: https://t.co/0dw7g63HdM
Looking forward to seeing your applications 🚀 @ecir2024@ir_glasgow
Working on topics related to graphs and IR? We might know what suits you 😎
We present the 1st International Workshop on Graph-Based Approaches in Information Retrieval (#IRonGraphs), co-located with #ECIR2024@ecir2024
Check out the workshop website: https://t.co/yY4ELx90eR
Are you attending @cikm2023? Join us tomorrow at the poster session! We'll be presenting our paper "Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems", at poster board #39 🙂
Paper in the ACM DL: https://t.co/xSZOyL1zJ3