Papers with user behavior modeling

2 papers
PUNR: Pre-training with User Behavior Modeling for News Recommendation (2023.findings-emnlp)

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Challenge: Existing news recommendation methods use pre-trained language models to produce news vectors and user vectors.
Approach: They propose an unsupervised pre-training paradigm with two tasks for user behavior modeling.
Outcome: The proposed model improves on the real-world news benchmark.
Is Your Language Model Ready for Monetization Decisions? (2026.findings-acl)

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Challenge: Existing benchmarks focus on shopping-centric scenarios and user-facing data, overlooking intermediate decision stages and robustness considerations.
Approach: They propose a multi-task benchmark to evaluate large language models in real-world monetization contexts.
Outcome: The proposed benchmark covers intent understanding, commercial matching, and user behavior modeling.

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