{"work":{"id":"7d7af2c4-98ea-4d25-997b-d3ec2bed3005","openalex_id":null,"doi":null,"arxiv_id":"2202.03772","raw_key":null,"title":"Particle Transformer for Jet Tagging","authors":null,"authors_text":"H","year":2022,"venue":"hep-ph","abstract":"Jet tagging is a critical yet challenging classification task in particle physics. While deep learning has transformed jet tagging and significantly improved performance, the lack of a large-scale public dataset impedes further enhancement. In this work, we present JetClass, a new comprehensive dataset for jet tagging. The JetClass dataset consists of 100 M jets, about two orders of magnitude larger than existing public datasets. A total of 10 types of jets are simulated, including several types unexplored for tagging so far. Based on the large dataset, we propose a new Transformer-based architecture for jet tagging, called Particle Transformer (ParT). By incorporating pairwise particle interactions in the attention mechanism, ParT achieves higher tagging performance than a plain Transformer and surpasses the previous state-of-the-art, ParticleNet, by a large margin. The pre-trained ParT models, once fine-tuned, also substantially enhance the performance on two widely adopted jet tagging benchmarks. The dataset, code and models are publicly available at https://github.com/jet-universe/particle_transformer.","external_url":"https://arxiv.org/abs/2202.03772","cited_by_count":null,"metadata_source":"pith","metadata_fetched_at":"2026-07-11T02:27:47.969912+00:00","pith_arxiv_id":"2202.03772","created_at":"2026-05-10T08:17:37.333827+00:00","updated_at":"2026-07-11T02:27:47.969912+00:00","title_quality_ok":false,"display_title":"Particle Transformer for Jet Tagging","render_title":"Particle Transformer for Jet Tagging"},"hub":{"state":{"work_id":"7d7af2c4-98ea-4d25-997b-d3ec2bed3005","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":31,"external_cited_by_count":null,"distinct_field_count":6,"first_pith_cited_at":"2023-03-25T16:23:27+00:00","last_pith_cited_at":"2026-07-07T20:16:49+00:00","author_build_status":"not_needed","summary_status":"needed","contexts_status":"needed","graph_status":"needed","ask_index_status":"not_needed","reader_status":"not_needed","recognition_status":"not_needed","updated_at":"2026-08-22T20:59:33.191935+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"method","n":6},{"context_role":"background","n":2},{"context_role":"dataset","n":1}],"polarity_counts":[{"context_polarity":"use_method","n":6},{"context_polarity":"background","n":2},{"context_polarity":"use_dataset","n":1}],"runs":{},"summary":{},"graph":{},"authors":[]}}