RSTLess group

Today @giulio_deras presented two works in the poster session of #ICTIR25 Eclipse: Contrastive Dimension Importance Estimation with Pseudo-Irrelevance Feedback for Dense Retrieval arxiv.org/pdf/2412.14967 and as a proxy presenter: QPP-RA: Aggregating Large Language Model Rankings

📢 Our TIM-Rec dataset has been accepted at the @ACMRecSys 2025 Resource Track! TIM-Rec tackles multi-item upselling in a Telco setting with sparse feedback, a real-world challenge for recommender systems. Congrats to the team @Alessandro91198 @_FedeSiciliano_ @fabreetseo! #RS

Long day in the office for @andreag_difra00, presenting at #IJCNN2025: A poster for the competition on Learning with Noisy Graph Labels Link Prediction with Physics-Inspired GNNs (GNN session) And served as session chair for both events! Link: arxiv.org/abs/2402.14802

On July 4th from 11 to 12.30, room Belli @giuditeodoro will present the work “A theoretical analysis of recommendation loss functions under negative sampling”. On July 2nd will present the Competition on Learning with Noisy Graph Labels from 10.30 to 12.30, room Manzoni. #IJCNN25

Next Monday will start the #IJCNN2025 conference! And our group will present lots of papers! On July 5th at 2.30 PM CET in Room Loyola @frances55037016 will present “Renormalized Graph Representations for Node Classification”. Preprint: arxiv.org/pdf/2306.00707 #Classication #ML

1/n While positional bias affects LLMs, it's actually not a real problem for practical RAG systems. In our new paper, we tackle the question “Do RAG Systems Suffer From Positional Bias?”