Harnessing Structural Context
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Harnessing Structural Context for Entity Alignment Foundation Models
Announce Type: new Abstract: Entity alignment (EA) aims to identify equivalent entities across heterogeneous knowledge graphs (KGs) and is a key component of knowledge fusion and cross-KG reasoning. The recent EA foundation model demonstrates that alignment knowledge, once pretrained, can be directly applied to diverse previously unseen KG pairs. However, it still underuses structural context in two places: cross-KG interaction is weak during encoding, and final candidate ranking still...
AutoSci: A Memory-Centric Agentic System for the Full Scientific Research Lifecycle
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Agentic Neuro-Symbolic Planning and Commissioning for Human-in-the-Loop Industrial Robotics with Digital Twins
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Show HN: Nucleus – A security-hardened, Nix-native container runtime
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Harnessing Generalist Agents for Contextualized Time Series
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At the Origins of Electroculture: A Retrodictive Modelling of Bertholon's 18th-Century Electrovegetometer in the Pre-Corona Regime
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Absorbing Complexity: An Interaction-Native Knowledge Harness for Financial LLM Agents
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LastAct: Trajectory-Guided Latest-Activity Localization for Real-Time Smart-Home Activity Recognition
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