Traditional search engines struggle to synthesize fragmented information for complex queries, while generative AI search engines face challenges in relevance, comprehensiveness, and presentation. To address these limitations, we introduce Xinyu AI Search, a novel system that incorporates a query-decomposition graph to...
Bo Tang, Junyi Zhu, Ang Li et al.· Proceedings of the 32nd ACM...· 0 citations
PaW is a Policy and World modeling co-training framework that adds auxiliary WM supervision to the same policy during RL, without changing the inference paradigm, and shows consistent improvements over strong RL baselines across models and RL algorithms.
Ning Lu, Baijiong Lin, Sheng-Cai Liu et al.· arXiv.org· 12 citations· ⚡2
This work proposes HIVE (History-Informed and online-VErified prompt selection), a dual-stage framework for data-efficient RL that utilizes historical reward trajectories for coarse selection and employs prompt entropy as a real-time proxy to prune instances with stale utility.
Jiahao Wu, Ning Lu, Sheng-Cai Liu et al.· 12 citations
CoPES is introduced, a cooperative coevolutionary method that decomposes the full parameter space into lower-dimensional subspaces and searches over them cooperatively to improve optimization efficiency and demonstrate an improved trade-off between memory requirements and training time for agentic LLM post-training und...
Zhiyuan Wang, Sheng-Cai Liu, Jiahao Wu et al.· 2 citations
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