Summary-token architectures such as Kwai Summary Attention (KSA) compress distant context into learnable Summary token per chunk, and hybrid variants interleave these layers with full attention to retain exact access to the original text. In such hybrid KSA-Full architecture, the interleaving inserted summary tokens ar...
OneRec Team, Chenglong Chu, Guo-Hong Mu et al.· 0 citations
A series of models are explored that connect item Semantic IDs with natural language in a unified representation space and seek to unlock the potential of natural-language chain-of-thought (CoT) reasoning for recommendation, including OneReason.
Jiang-Xia Cao, Hao Peng, Wen-Long Xu et al.· 0 citations
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
The sample efficiency and scalability of RL post-training for video MLLMs and introduces OraRL, a decoupled advantage estimator that scales with model size and data, surpassing its backbone from 0.8B to 9B and GRPO up to 100k prompts.
Yun-Heng Li, Guo-Hong Mu, Hao Li et al.· 1 citation
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