Accepted Papers

We are pleased to announce the papers accepted to EARL 2026. All accepted papers will be presented orally at the workshop on 8 November 2026 (times are local Rome time, CET). See the full schedule for the complete programme.

Long Talks

• Beyond Posts: Recommending Conversations in Threads Feed — Xiuyan Ni, Qing Feng, Eric He, Akhil Nadigatla, Adam Kozdrowicz, Emerson Wenzel, Runbo Jiang, Nicholas Joodi, Xiaoyu Cao, Zichao Li, Joy Qiu, Namrita Perincherry, Jiangxue Xu, Jiaxin Ying, Feifei Yu, Anthony D’Souza, Shuting Wang, Ivan Ji and Shujian Bu (09:40–10:00).
• Dialogue Generation for Conversational Recommendation Using User Search Interactions and Knowledge Graphs — Minsung Hwang, Donggyu Yoon, Gowoon Hwang, Kwanghee Jang and Joyce Jiyoung Whang (11:30–11:50).
• Format Compliance without Detectable Preference Gain: A Paired Audit of Post-Trained LLM Recommenders — Shiming Xie (11:50–12:10)

Short Talks

• From Raw IDs to Semantic Planning: How Recommender Systems Utilize Information at Scale — Changhong Jin, Shiqiu Yang, Roger Zhe Li, Yingjie Niu, Aghiles Salah, Mete Sertkan, Zheng Ju, Xingsheng Guo, Huifeng Guo, Ruihai Dong and Barry Smyth (10:00–10:10).
• Encoded but Exposed: Language Embeddings can Reveal More Than They Should in Recommender Systems — Linda Beková and Rodrigo Alves (10:10–10:20).
• When to Ask: A Framework for Interruption-Aware Conversational Recommendation — Sanjana Arun (10:20–10:30).
• Validity Lag: Why LLM Recommender Evaluation Keeps Failing the Same Way — Shiming Xie (10:30–10:40)
• Persona Aware Session-Based Recommendation with LLM-Enhanced Knowledge Graphs — Muskan Gupta, Priyanka Gupta and Jyotsana Khatri (12:10–12:20).
• From a Large-Scale Teacher to Efficient Multimodal Students for Search Relevance Prediction — Tomasz Gniazdowski, Mohammadreza Momenifar, Nadia Vase, Shahram Khadivi, Wiktor Walentynowicz, Nicola Ueffing, Jan Pawłowski, Piotr Szymański and Abraham Bagherjeiran (12:20–12:30).
• Preprocessing Choices in Fine-Tuning Data Matter: Utility and Demographic Sensitivity in LLM-Based Recommendation — Furkan Yasir Goksu, Yaren Yilmaz and Şule Gündüz Öğüdücü (12:30–12:40).
• Revisiting Generative vs. Dense Retrieval: A Static Value Prior Reverses the Gap — Renbo Tu, Yang Liu and Shuying Sun (12:40–12:50).