Author

Chang-Xin Lao

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#artificial intelligence Review Sep 2026

Advancing Model Research in AgentX: Long-Horizon Autonomy for Industrial Recommender Systems

Sustaining industrial recommendation research requires using the results of one experiment to decide what to investigate next. We present AgentX-Model, the next generation of AgentX's model research framework, which connects proposal development and model experimentation within sandboxes defined by business inputs and...

Shuang Yang, Zi-Jie Zhuang, Chang-Xin Lao et al. · 0 citations

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