HEPTv2 achieves 98.6% double-majority tracking efficiency at 0.8% fake rate with ~15 ms inference and 0.4 GB memory on TrackML using an end-to-end point transformer with locality-sensitive hashing.
High Pileup Particle Tracking with Object Condensation
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Double metric learning learns two embeddings per node to build directed graphs with chain connections, yielding better performance than single metric learning for high-pT particles and accurate edge direction prediction in ATLAS ITk simulations.
citing papers explorer
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HEPTv2: End-to-End Efficient Point Transformer for Charged Particle Reconstruction
HEPTv2 achieves 98.6% double-majority tracking efficiency at 0.8% fake rate with ~15 ms inference and 0.4 GB memory on TrackML using an end-to-end point transformer with locality-sensitive hashing.
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Double Metric Learning for Building Directed Graphs with Chain Connections for the ATLAS ITk Detector
Double metric learning learns two embeddings per node to build directed graphs with chain connections, yielding better performance than single metric learning for high-pT particles and accurate edge direction prediction in ATLAS ITk simulations.