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Haoyan Liu

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Sep 2026

Turning Cold Entities Warm: LLM-Based User and Item Interaction Simulation for Recommendations

Recommendation throughout the cold-start period remains a challenge in recommender systems. Strictly cold entities (users/items) have no interactions, while warm-up entities only have a few unreliable interactions. Strict cold-start methods typically overlook warm-up entities, while warm-up methods are generally not de...

Hao Chen, Li-Jia Chen, Huan Gong et al. · 0 citations
#artificial intelligence Review May 2026

MBABench: Evaluating LLM Agents on End-to-End Spreadsheet Tasks in Finance

This work provides one of the first evaluations of agents on end-to-end spreadsheet tasks, focusing on economically critical financial workflows such as modeling and scenario analysis, and develops an evaluation taxonomy comprising three dimensions: Accuracy, Formula, and Format, each comprising fine-grained criteria t...

Thomson Yen, Julian Poeltl, Harshith Srinivas Gear et al. · 1 citation

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