This work introduces AVP (Action with Visual Primitives), an end-to-end architecture that implements this visual-primitive-centric interface: the VLM infers the next-stage target and emits visual-primitive tokens that condition a flow-matching action expert, with supervision derived from end-effector kinematics.
HSMLog, a two-stage framework for HSM log anomaly detection with retrieval-grounded behavioral analysis, is presented, demonstrating effective anomaly alerting and incident triage in the studied setting.
This paper formalizes KV management as a causal system of three primitives: KV Admission, Selection, and Eviction, and instantiate KV Admission via Write-Gated KV (WG-KV), a lightweight mechanism that learns to predict token utility before cache entry.
Yen-Chieh Huang, Rui Fang, Ming-Syan Chen et al.· 2 citations
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