Omni-modal assistants must remember not only what users say, but also what they show and convey. Existing long-term memory benchmarks are mostly text-and-image or report a single end-to-end score, so they cannot locate whether evidence is lost when it is represented, retrieved, delivered, or read. We introduce MOSAIC,...
Hong Ting Tsang, Bo-Yi Zhang, Haoyu Huang et al.· 0 citations
Repeated event forecasting requires extracting predictive signals from noisy evidence and evaluating their value across successive decisions. We introduce JockeyBench, a benchmark and evaluation protocol that studies this problem through historical Japanese horse racing. The protocol combines time-gated evidence, price...
Zhong-Wei Xie, Xing-Su Li, Jing Yu et al.· 0 citations
This survey focuses on methods that augment LLMs with such parametric memory at deployment: a memory-bearing parameter object is plugged into the forward pass during inference, whether it is acquired before or during deployment.
Haoyu Huang, Zhong-Wei Xie, Jiaxin Bai et al.· 0 citations
AgentIdeaBench is introduced, a multidisciplinary benchmark that evaluates scientific ideation under two matched settings, static observation and active exploration, and Scientific World Modeling is explored, a generation-time loop that refines a draft hypothesis through structured thought experiments.
Yunxiang Mo, Tianshi ZHENG, Yi-Sen Gao et al.· 1 citation
It is shown that broader retrieval benefits visual DLM-RAG through selective evidence admission rather than unconditional evidence expansion, and the Entropy-Based Candidate Filter (ECF), a training-free evidence-admission framework is proposed, shows that broader retrieval benefits visual DLM-RAG through selective evi...
Jiankun Wang, Yi-Sen Gao, Zi-Wei Zhang et al.· 0 citations
Temporal-Distance-JEPA narrows the train--plan gap for JEPA world-model planners by discovering temporal progress structure in offline logs and co-designing cost form with plan-time deployment.
VisualPatchWorld is introduced, which represents world dynamics as code and first selects a qualitative dynamical form with short active probes, then fits that form's free parameters from recorded state-action traces by minimizing multi-step prediction error.
Jiaxin Bai, Jia–Jie Xiong· arXiv.org· 0 citations
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