Author

Jiangxia Cao

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Jul 2026

Unifying Generative Recall and Multi-Objective Ranking in a Single Decoder-Only Sequence

This work proposes UniR, a decoder-only Transformer that unifies Generative and Multi-Objective ranking within a single heterogeneous sequence comprising user context, SID trajectory, and item features, validating the practicality of unified model in large-scale recommendation systems.

Ruo-Chen Yang, Shuang Wen, Peng-Bo Xu et al. · arXiv.org · 1 citation

Jul 2026

RecoReward: Recommender-Guided Multimodal Description Generation for Recommendation

These results show that RecoReward trains the MLLM to produce item features that benefit downstream recommendation while retaining content-only serving, and shows that RecoReward-9B outperforms its Qwen3.5-9B baseline and all other evaluated models across seven recall metrics.

Guohong Mu, Yue-Yang Liu, Jiangxia Cao et al. · arXiv.org · 0 citations