JetFormer: A Scalable and Efficient Transformer for Jet Tagging from Offline Analysis to FPGA Triggers

arXiv:2601.17215 · cs.LG, hep-ex · Submitted 2026-01-23 · Read on arXiv

cs.LG, hep-ex

Submitted: 2026-01-23

Updated: 2026-01-23

Comments: 15 pages,

Code: https://github.com/walkieq/JetFormer

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 63× in this paper · explained in 2 episodes
• Accuracy — 56× in this paper · explained in 1 episode
• Quantization — 33× in this paper · explained in 12 episodes
• Pruning — 24× in this paper · explained in 4 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• AUC — 7× in this paper · explained in 2 episodes
• Generalization — 6× in this paper · explained in 13 episodes
• Transformer Architecture — 5× in this paper · explained in 2 episodes
• Transformer Models — 5× in this paper · explained in 2 episodes
• Large Hadron Collider — 4× in this paper
• Quantization-Aware Training — 3× in this paper · explained in 3 episodes
• Activation Function — 2× in this paper · explained in 1 episode
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• GNNs — 2× in this paper · explained in 2 episodes
• Graph Neural Networks (GNNs) — 2× in this paper · explained in 7 episodes
• Multi-objective Optimization — 2× in this paper · explained in 4 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Architectural Adaptation — 1× in this paper · explained in 1 episode
• Bayesian Optimization — 1× in this paper · explained in 3 episodes
• Covariate Shift — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Feature Engineering — 1× in this paper · explained in 3 episodes
• Multi-Layer Perceptron — 1× in this paper
• Multi-Level Intermediate Representation — 1× in this paper
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Resource Constraints — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• An Attention Based Neural Network for Jet Tagging
• Fast Jet Tagging with MLP-Mixers on FPGAs
• Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning
• Decoupled Weight Decay Regularization
• BitNet: Scaling 1-bit Transformers for Large Language Models
• Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets

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