Recent Publications¶
This is an automatically compiled list of papers which have been added to the living review that were made public within the previous 4 months at the time of updating. This is not an exhaustive list of released papers, and is only able to find those which have both year and month data provided in the bib reference.
June 2026¶
- Conformal calibration and look-elsewhere effect in anomaly detection for new-physics searches (2026)
May 2026¶
- Generative Models and Statistical Validation (2026)
- Deep-learning-based low-energy trigger algorithms for the Hyper-Kamiokande experiment (2026)
- Model-Agnostic Signal Discovery with Machine Learning: Bridging the Gap Between Theory and Practice (2026)
- Exploring Low Energy Excess in MINER with sapphire detectors using Convolutional Variational Autoencoder (CVAE) (2026)
- Neural Scaling Laws for Jet Generation (2026)
- First steps towards gauge-independent vortex identification through machine learning (2026)
- Search for pair-produced vector-like \(T\)-quarks decaying into \(Ht\) final states in the lepton-plus-jets channel in \(pp\) collisions at \(\sqrt{s}\) (2026)
- Solitonic Construction of Artificial Neural Networks from Nonlinear Field Theory (2026)
- Particle-Lund Multimodality in Jet Taggers (2026)
- Flow-Based Global Proposals for Monte Carlo Sampling in SU(2) Lattice Gauge Theory (2026)
- Experiments in Agentic AI for Science (2026)
- Equation of State at High Baryon Densities from a Thermodynamically Informed Neural Network (2026)
- Deep Neural Networks for Heavy Lepton-Flavor-Violating Higgs Searches at the LHC (2026)
- Normalizing flows for all-orders QED corrections in lattice field theory (2026)
- Symbolic Classification-Enabled LHC Limits Online BSM Global Fits (2026)
- Patch Hierarchical Attention Transformer for Efficient Particle Jet Tagging (2026)
- Enhanced Ionization Charge Identification in the Short-Baseline Neutrino Program Neutrino Detectors with Deep Neural Networks (2026)
- Probing SMEFT Operators through \(t\bar{t}t\bar{t}\) Production with Hyper-Graph Neural Networks at the LHC (2026)
- Quantum enhanced identification of boosted jets with quantum graph neural networks (2026)
- ML-based Fast Simulation of FARICH Responses (2026)
- RooAgent: An LLM Agent for Root-Based High Energy Physics Analysis (2026)
- Nested-GPT for variable-multiplicity parton showers: A case study in the resummation of non-global logarithms (2026)
- A flow-matching generative model for event-by-event jet-induced hydro response in high-energy heavy-ion collisions (2026)
- Geometric algebra as the input language of collider foundation models (2026)
- Surrogate Neural Architecture Codesign Package (SNAC-Pack) (2026)
- Double Metric Learning for Building Directed Graphs with Chain Connections for the ATLAS ITk Detector (2026)
- AI-Driven Discovery of Information-Efficient Collider Observables for Interference Measurements (2026)
- Collider-Bench: Benchmarking AI Agents with Particle Physics Analysis Reproduction (2026)
- Neural Network Generalized Parton Distributions (NNGPD) (2026)
- Search for pair production of additional neutral scalars within the Inert Doublet Model in a final state with two electrons or two muons in proton-proton collisions at \(\sqrt{s}\) (2026)
- Novel Machine Learning Methods to Improve Z Pole Integrated Luminosity at Future Colliders [DOI] (2026)
- DNN predictions for pp reference \(p_\mathrm{T}\) spectra at unmeasured \(\sqrt{s}\) (2026)
- Operator Spectroscopy of Trained Lattice Samplers (2026)
- Anomalies in Neural Network Field Theory (2026)
- CaloArt: Large-Patch x-Prediction Diffusion Transformers for High-Granularity Calorimeter Shower Generation (2026)
- Machine Learning for neutron source distributions (2026)
- Inferring identified hadron production in \(pp\) collisions with physics-informed machine learning at the LHC (2026)
- Optimizing Yukawa couplings to suppress Dimension-five Proton Decay in \(SU(5)\) GUT (2026)
- Dissecting Jet-Tagger Through Mechanistic Interpretability (2026)
- Uncertainty in Physics and AI: Taxonomy, Quantification, and Validation (2026)
- Unbinned extraction of \(γ\) from \(B\to DK\) with normalizing flows (2026)
- Neural Network Representation of Generalized Parton Distributions (NNGPD) (2026)
- Testing machine-learned distributions against Monte Carlo data for the QCD chiral phase transition (2026)
- When Does Critique Improve AI-Assisted Theoretical Physics? SCALAR: Structured Critic--Actor Loop for Agentic Reasoning (2026)
- NEXT Simulation Dataset for AI Summer School UC Irvine 2026 [DOI] (2026)
- Learning Minimal-Deviation Corrections for Multi-Dimensional Mismodelling in HEP Simulations (2026)
- Uncovering Hidden Systematics in Neural Network Models for High Energy Physics (2026)
- Transfer Learning Across Fast- and Full-Simulation Domains in High-Energy Physics (2026)
- First next-to-next-to-leading-order extraction of fragmentation functions for Lambda hyperons (2026)
- TMDs in the Lens of Generative AI: A Pixel-Based Approach to Partonic Imaging (2026)
- Diffusion model for SU(N) gauge theories (2026)
- Lattice fermion formulation via Physics-Informed Neural Networks: Ginsparg-Wilson relation and Overlap fermions [DOI] (2026)
- BRICKS: Compositional Neural Markov Kernels for Zero-Shot Radiation-Matter Simulation (2026)
- Toward a Community Roadmap for High Energy Physics and Artificial Intelligence in China and Beyond (2026)
- Data-Driven, Geometry-Aware Optimal-Transport Calibration of Flavor Tagger (2026)
- Reconstructing conformal field theoretical compositions with Transformers (2026)
- A real-time demonstrator of track reconstruction with FPGAs at LHCb (2026)
- HepScript: A Dual-Use DSL for Human-AI Collaborative Data Analysis Workflows in High-Energy Physics (2026)
- Cascade Pipeline for Leading-Order Matrix Element Evaluation on AMD Versal AI Engine Arrays (2026)
- From Experimental Limits to Physical Insight: A Retrieval-Augmented Multi-Agent Framework for Interpreting Searches Beyond the Standard Model (2026)
April 2026¶
- Optimal Architecture and Fundamental Bounds in Neural Network Field Theory (2026)
- Optimisation of a silicon-tungsten electromagnetic calorimeter energy response to photons (2026)
- Machine Learning Enables Real-Time Waveform Decomposition for Dual-Readout Calorimetry (2026)
- Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane (2026)
- Search for electroweakinos in compressed-spectrum scenarios with low-momentum isolated tracks in proton-proton collisions at \(\sqrt{s}\) (2026)
- Big Dipper, Help Me Find A Way -- Dip-hunting at hadron colliders (2026)
- Physics-Informed Neural Networks for Solving Two-Flavor Neutrino Oscillations in Vacuum and Matter Environments for Atmospheric and Reactor Neutrinos (2026)
- Incorporating Inelasticity Reconstruction into Neutrino Mass Ordering Studies with IceCube (2026)
- Passage of particles through matter and the effective straggling-function: High-fidelity accelerated simulation via Physics-Informed Machine Learning (2026)
- Machine Learning for Multi-messenger Probes of New Physics and Cosmology: A Review and Perspective [DOI] (2026)
- Four-dimensional QCD equation of state from a quasi-parton model with physics-informed neural networks (2026)
- Dr.Sai: An agentic AI for real-world physics analysis at BESIII (2026)
- HGQ-LUT: Fast LUT-Aware Training and Efficient Architectures for DNN Inference [DOI] (2026)
- Jet Quenching Identification via Supervised Learning in Simulated Heavy-Ion Collisions [DOI] (2026)
- Analytical and Machine Learning Methods for Model Discernment at CE\(ν\)NS Experiments (2026)
- Kitchen Sink Anomaly Detection (2026)
- Masked-Token Prediction for Anomaly Detection at the Large Hadron Collider (2026)
- Phenomenological Detector Design and Optimization in Vertically-Integrated Differentiable Full Simulations with Agentic-AI (2026)
- How Invisible: Regressing The Key Model Parameter for Semi-visible Jet Searches (2026)
- Neural posterior estimation of the neutrino direction in IceCube using transformer-encoded normalizing flows on the sphere (2026)
- Using Graph Neural Networks for hadronic clustering and to reduce beam background in the Belle{\textasciitilde}II electromagnetic calorimeter (2026)
- A Scientific Human-Agent Reproduction Pipeline [DOI] (2026)
- Fine-Tuning Small Reasoning Models for Quantum Field Theory (2026)
- RL-ABC: Reinforcement Learning for Accelerator Beamline Control (2026)
- Federated Learning with Quantum Enhanced LSTM for Applications in High Energy Physics (2026)
- Proton Structure from Neural Simulation-Based Inference at the LHC (2026)
- AI-assisted modeling and Bayesian inference of unpolarized quark transverse momentum distributions from Drell-Yan data (2026)
- Enhancing Event Reconstruction in Hyper-Kamiokande with Machine Learning: A ResNet Implementation (2026)
- Cross-Domain Transfer with Particle Physics Foundation Models: From Jets to Neutrino Interactions (2026)
- An AI-based Detector Simulation and Reconstruction Model for the ALEPH Experiment at LEP (2026)
- Machine learning for four-dimensional SU(3) lattice gauge theories (2026)
- Radiatively Corrected Hybrid Inflation: Parameter Scans and Machine Learning with ACT and Future CMB Experiments (2026)
- Machine Learning Study on Single Production of a Singlet Vector-like Lepton at the Large Hadron Collider [DOI] (2026)
- Particle transformers for identifying Lorentz-boosted Higgs bosons decaying to a pair of W bosons (2026)
- Filtering hits for speeding up online track reconstruction at hadron colliders (2026)
- Scalable Generative Sampling and Multilevel Estimation for Lattice Field Theories Near Criticality (2026)
- New Deep Learning Data Analysis Method for PROSPECT using GAPE: Genetic Algorithm Powered Evolution (2026)
- Lecture notes on Machine Learning applications for global fits (2026)
- ML for the hKLM at the 2nd Detector [DOI] (2026)
- Diffusion-Based Point-Cloud Generation of Heavy-Ion Events (2026)
- Exotic Higgs Decays at a Muon Collider (2026)
- Neural network interpolators for Wilson loops (2026)
- Quantum-Inspired Tensor Network Autoencoders for Anomaly Detection: A MERA-Based Approach (2026)
- Towards foundation-style models for energy-frontier heterogeneous neutrino detectors via self-supervised pre-training (2026)
- Learning to Unscramble Feynman Loop Integrals with SAILIR (2026)
- Holographic entanglement entropy, Wilson loops, and neural networks (2026)
- Monte Carlo Event Generation with Continuous Normalizing Flows (2026)
- Generative models on phase space (2026)
- Applying Self-organizing Maps to the Inverse Problem (2026)
- Probing Freeze-In Dark Matter via a Spin-2 Portal at the LHC with Vector Boson Fusion and Machine Learning (2026)
- Probing Proton Structure via Physics-Guided Neural Networks in Holographic QCD (2026)
- Descending into the Modular Bootstrap (2026)
- Topological Effects in Neural Network Field Theory (2026)
- Many Wrongs Make a Right: Leveraging Biased Simulations Towards Unbiased Parameter Inference (2026)
- JetPrism: diagnosing convergence for generative simulation and inverse problems in nuclear physics [DOI] (2026)
- Retrieval-Augmented Question Answering over Scientific Literature for the Electron-Ion Collider (2026)