output
20022026
most citedGravitational Waves and Gamma-rays from a Binary Neutron Star Merger: GW170817 and GRB 170817A

3.6k citations

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11 papers · 1 filter

cs.IR2026

TRACE: A Conversational Framework for Sustainable Tourism Recommendation with Agentic Counterfactual Explanations

Ashmi Banerjee, Adithi Satish, Wolfgang Wörndl +1

Traditional conversational travel recommender systems primarily optimize for user relevance and convenience, often reinforcing popular, overcrowded destinations and carbon-intensiv…

cs.IR202515 cited

Do LLMs Memorize Recommendation Datasets? A Preliminary Study on MovieLens-1M

Dario Di Palma, Felice Antonio Merra, Maurizio Sfilio +3

Large Language Models (LLMs) have become increasingly central to recommendation scenarios due to their remarkable natural language understanding and generation capabilities. Althou…

cs.IR20254 cited

SynthTRIPs: A Knowledge-Grounded Framework for Benchmark Query Generation for Personalized Tourism Recommenders

Ashmi Banerjee, Adithi Satish, Fitri Nur Aisyah +2

Tourism Recommender Systems (TRS) are crucial in personalizing travel experiences by tailoring recommendations to users' preferences, constraints, and contextual factors. However,…

cs.IR202423 cited

EB-NeRD: A Large-Scale Dataset for News Recommendation

Johannes Kruse, Kasper Lindskow, Saikishore Kalloori +6

Personalized content recommendations have been pivotal to the content experience in digital media from video streaming to social networks. However, several domain specific challeng…

cs.IR202412 cited

RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations

Johannes Kruse, Kasper Lindskow, Saikishore Kalloori +6

The RecSys Challenge 2024 aims to advance news recommendation by addressing both the technical and normative challenges inherent in designing effective and responsible recommender…

cs.IR20248 cited

Enhancing Sequential Music Recommendation with Personalized Popularity Awareness

Davide Abbattista, Vito Walter Anelli, Tommaso Di Noia +2

In the realm of music recommendation, sequential recommender systems have shown promise in capturing the dynamic nature of music consumption. Nevertheless, traditional Transformer-…