Jet Tagging

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

21 shown of 21 papers with code (45 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• ParticleNet: Jet Tagging via Particle Clouds
  22 Feb 2019 6 repositories listed Syntology ran 2 of 23 samples · 21 unverified · 1 pointer-only (licence)
  How to represent a jet is at the core of machine learning on jet physics.
• Gradient-based Automatic Mixed Precision Quantization for Neural Networks On-Chip
  1 May 2024 2 repositories listed
  Model size and inference speed at deployment time, are major challenges in many deep learning applications.
• Guided Graph Compression for Quantum Graph Neural Networks
  11 Jun 2025 1 repository listed
  The compression is guided to enhance the performance of a downstream classification task, which can be applied either with a quantum or a classical classifier.
• Interpreting Transformers for Jet Tagging
  4 Dec 2024 1 repository listed Syntology ran 1 of 4 samples · 3 unverified · 4 pointer-only (licence)
  Machine learning (ML) algorithms, particularly attention-based transformer models, have become indispensable for analyzing the vast data generated by particle physics experiments like ATLAS and CMS at the CERN LHC.
• Lie-Equivariant Quantum Graph Neural Networks
  22 Nov 2024 1 repository listed Syntology ran 0 of 5 samples · 5 unverified · 5 pointer-only (licence)
  Discovering new phenomena at the Large Hadron Collider (LHC) involves the identification of rare signals over conventional backgrounds.
• OmniJet-α: The first cross-task foundation model for particle physics
  8 Mar 2024 1 repository listed
  This is the first successful transfer between two different and actively studied classes of tasks and constitutes a major step in the building of foundation models for particle physics.
• SymbolNet: Neural Symbolic Regression with Adaptive Dynamic Pruning for Compression
  18 Jan 2024 1 repository listed
  In this work, we propose SymbolNet, a neural network approach to symbolic regression specifically designed as a model compression technique, aimed at enabling low-latency inference for high-dimensional inputs on custom…
• A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks
  30 Nov 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  In this paper, we perform a fair and comprehensive comparison between classical graph neural networks (GNNs) and equivariant graph neural networks (EGNNs) and their quantum counterparts: quantum graph neural networks…
• JetLOV: Enhancing Jet Tree Tagging through Neural Network Learning of Optimal LundNet Variables
  24 Nov 2023 1 repository listed Syntology ran 4 of 5 samples · 1 unverified
  Machine learning has played a pivotal role in advancing physics, with deep learning notably contributing to solving complex classification problems such as jet tagging in the field of jet physics.
• Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation
  23 Nov 2023 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  The challenging environment of real-time data processing systems at the Large Hadron Collider (LHC) strictly limits the computational complexity of algorithms that can be deployed.
• 19 Parameters Is All You Need: Tiny Neural Networks for Particle Physics
  24 Oct 2023 1 repository listed Syntology ran 17 of 17 samples · 0 unverified
  As particle accelerators increase their collision rates, and deep learning solutions prove their viability, there is a growing need for lightweight and fast neural network architectures for low-latency tasks such as…
• PCN: A Deep Learning Approach to Jet Tagging Utilizing Novel Graph Construction Methods and Chebyshev Graph Convolutions
  12 Sep 2023 1 repository listed
  To learn best from this representation, we design Particle Chebyshev Network (PCN), a graph neural network (GNN) using Chebyshev graph convolutions (ChebConv).
• Graph Structure from Point Clouds: Geometric Attention is All You Need
  31 Jul 2023 1 repository listed
  The use of graph neural networks has produced significant advances in point cloud problems, such as those found in high energy physics.
• Do graph neural networks learn traditional jet substructure?
  17 Nov 2022 1 repository listed Syntology ran 0 of 7 samples · 7 unverified
  At the CERN LHC, the task of jet tagging, whose goal is to infer the origin of a jet given a set of final-state particles, is dominated by machine learning methods.
• BIP: Boost Invariant Polynomials for Efficient Jet Tagging
  17 Jul 2022 1 repository listed
  Deep Learning approaches are becoming the go-to methods for data analysis in High Energy Physics (HEP).
• Improving Robustness of Jet Tagging Algorithms with Adversarial Training
  25 Mar 2022 1 repository listed
  We investigate the classifier response to input data with injected mismodelings and probe the vulnerability of flavor tagging algorithms via application of adversarial attacks.
• Particle Transformer for Jet Tagging
  8 Feb 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Based on the large dataset, we propose a new Transformer-based architecture for jet tagging, called Particle Transformer (ParT).
• Point Cloud Transformers applied to Collider Physics
  9 Feb 2021 1 repository listed
  Methods for processing point cloud information have seen a great success in collider physics applications.
• Jet tagging in the Lund plane with graph networks
  15 Dec 2020 1 repository listed
  The identification of boosted heavy particles such as top quarks or vector bosons is one of the key problems arising in experimental studies at the Large Hadron Collider.
• Variational Autoencoders for Anomalous Jet Tagging
  3 Jul 2020 1 repository listed Syntology ran 1 of 9 samples · 8 unverified
  To build a performant mass-decorrelated anomalous jet tagger, we propose the Outlier Exposed VAE (OE-VAE), for which some outlier samples are introduced in the training process to guide the learned information.
• Jet-Images -- Deep Learning Edition
  16 Nov 2015 1 repository listed Syntology ran 0 of 16 samples · 16 unverified
  Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based…

Syntology lines on 11 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.