Snippet-Driven Supply Chain Discovery with LLMs: Scaling Visibility in China

arXiv:2605.27845 · cs.SI, cs.AI, physics.soc-ph · Submitted 2026-05-27 · Read on arXiv

cs.SI, cs.AI, physics.soc-ph

Submitted: 2026-05-27

Updated: 2026-05-27

Terminology

• Benchmark — 15× in this paper · explained in 2 episodes
• Knowledge Graph — 14× in this paper · explained in 7 episodes
• Provenance — 9× in this paper · explained in 4 episodes
• Knowledge graphs — 5× in this paper · explained in 2 episodes
• Graph Construction — 2× in this paper · explained in 3 episodes
• Human-in-the-Loop — 2× in this paper · explained in 3 episodes
• Information Asymmetry — 2× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Conference on Automation Science and Engineering — 1× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes

Related papers

• Linking Scalar-Intensity Language to Structural Polarization with Validated Signed-Network Measures
• Detection and Characterization of Coordinated Online Behavior: A Survey
• Omega-N: Interpretable Structural Node Descriptors and Their Applicability Domain
• Simplify to Amplify: Achieving Information-Theoretic Bounds with Fewer Steps in Spectral Community Detection
• Transmission Neural Networks: Inhibitory and Excitatory Connections
• A family of graph GOSPA metrics for graphs with different sizes