latest updates. next in december (#230)

* latest updates. next in december

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Fix copy error

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

HEPML.bib

@@ -1,6 +1,6 @@
 # HEPML Papers
 
-% November 08, 2024
+% November 12, 2024
 @article{Cornell:2024dki,
     author = "Cornell, Alan S. and Fuks, Benjamin and Goodsell, Mark D. and Ncube, Anele M.",
     title = "{Improving smuon searches with Neural Networks}",
@@ -11,6 +11,75 @@ @article{Cornell:2024dki
     year = "2024"
 }
 
+% November 12, 2024
+@article{Richter-Was:2024jxn,
+    author = "Richter-Was, E. and Yerniyazov, T. and Was, Z.",
+    title = "{Pseudo-observables and Deep Neural Network for mixed CP -- H to tau tau decays at LHC}",
+    eprint = "2411.06216",
+    archivePrefix = "arXiv",
+    primaryClass = "hep-ph",
+    reportNumber = "IFJPAN-IV-2024-12",
+    month = "11",
+    year = "2024"
+}
+
+% November 12, 2024
+@article{Kawai:2024pws,
+    author = "Kawai, Shinsuke and Okada, Nobuchika",
+    title = "{Truth, beauty, and goodness in grand unification: a machine learning approach}",
+    eprint = "2411.06718",
+    archivePrefix = "arXiv",
+    primaryClass = "hep-ph",
+    month = "11",
+    year = "2024"
+}
+
+% November 12, 2024
+@article{CMS:2024jdl,
+    author = "{CMS Collaboration}",
+    title = "{Reweighting simulated events using machine-learning techniques in the CMS experiment}",
+    eprint = "2411.03023",
+    archivePrefix = "arXiv",
+    primaryClass = "hep-ex",
+    reportNumber = "CMS-MLG-24-001, CERN-EP-2024-269",
+    month = "11",
+    year = "2024"
+}
+
+% November 12, 2024
+@article{Smith:2024lxz,
+    author = "Smith, Dylan and Ghosh, Aishik and Liu, Junze and Baldi, Pierre and Whiteson, Daniel",
+    title = "{Fast multi-geometry calorimeter simulation with conditional self-attention variational autoencoders}",
+    eprint = "2411.05996",
+    archivePrefix = "arXiv",
+    primaryClass = "hep-ex",
+    month = "11",
+    year = "2024"
+}
+
+% November 12, 2024
+@article{VanStroud:2024fau,
+    author = "Van Stroud, Samuel and Duckett, Philippa and Hart, Max and Pond, Nikita and Rettie, S\'ebastien and Facini, Gabriel and Scanlon, Tim",
+    title = "{Transformers for Charged Particle Track Reconstruction in High Energy Physics}",
+    eprint = "2411.07149",
+    archivePrefix = "arXiv",
+    primaryClass = "hep-ex",
+    month = "11",
+    year = "2024"
+}
+
+% November 08, 2024
+@article{ATLAS:2024mrr,
+    author = "{ATLAS Collaboration}",
+    title = "{Search for vector-like leptons coupling to first- and second-generation Standard Model leptons in $pp$ collisions at $\sqrt{s}=13$ TeV with the ATLAS detector}",
+    eprint = "2411.07143",
+    archivePrefix = "arXiv",
+    primaryClass = "hep-ex",
+    reportNumber = "CERN-EP-2024-296",
+    month = "11",
+    year = "2024"
+}
+
 % November 06, 2024
 @article{Heller:2024onk,
     author = "Heller, Nick and Ilten, Phil and Menzo, Tony and Mrenna, Stephen and Nachman, Benjamin and Siodmok, Andrzej and Szewc, Manuel and Youssef, Ahmed",

README.md

@@ -445,6 +445,7 @@ This review was built with the help of the HEP-ML community, the [INSPIRE REST A
 
 ####  BSM particles and models
 
+* [Pseudo-observables and Deep Neural Network for mixed CP -- H to tau tau decays at LHC](https://arxiv.org/abs/2411.06216) (2024)
 * [Improving smuon searches with Neural Networks](https://arxiv.org/abs/2411.04526) (2024)
 * [Machine-Learning Analysis of Radiative Decays to Dark Matter at the LHC](https://arxiv.org/abs/2410.13799) (2024)
 * [Machine learning tagged boosted dark photon: A signature of fermionic portal matter at the LHC](https://arxiv.org/abs/2410.06925) (2024)
@@ -527,6 +528,7 @@ This review was built with the help of the HEP-ML community, the [INSPIRE REST A
 
 ####  Particle identification
 
+* [Transformers for Charged Particle Track Reconstruction in High Energy Physics](https://arxiv.org/abs/2411.07149) (2024)
 * [Detecting highly collimated photon-jets from Higgs boson exotic decays with deep learning](https://arxiv.org/abs/2401.15690) (2024)
 * [Machine-learning-based particle identification with missing data](https://arxiv.org/abs/2401.01905) [[DOI](https://doi.org/10.1140/epjc/s10052-024-13047-3)] (2024)
 * [Study of residual artificial neural network for particle identification in the CEPC high-granularity calorimeter prototype](https://arxiv.org/abs/2310.09489) [[DOI](https://doi.org/10.1088/1748-0221/19/04/P04033)] (2023)
@@ -1051,6 +1053,7 @@ This review was built with the help of the HEP-ML community, the [INSPIRE REST A
 
 ###  Calibration
 
+* [Reweighting simulated events using machine-learning techniques in the CMS experiment](https://arxiv.org/abs/2411.03023) (2024)
 * [Vertex Imaging Hadron Calorimetry Using AI/ML Tools](https://arxiv.org/abs/2408.15385) (2024)
 * [ML-based Calibration and Control of the GlueX Central Drift Chamber](https://arxiv.org/abs/2403.13823) (2024)
 * [A Comparison of Deep Learning Models for Proton Background Rejection with the AMS Electromagnetic Calorimeter](https://arxiv.org/abs/2402.16285) (2024)
@@ -1464,6 +1467,7 @@ This review was built with the help of the HEP-ML community, the [INSPIRE REST A
 
 ###  (Variational) Autoencoders
 
+* [Fast multi-geometry calorimeter simulation with conditional self-attention variational autoencoders](https://arxiv.org/abs/2411.05996) (2024)
 * [CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation](https://arxiv.org/abs/2410.21611) (2024)
 * [Calo-VQ: Vector-Quantized Two-Stage Generative Model in Calorimeter Simulation](https://arxiv.org/abs/2405.06605) (2024)
 * [Deep Generative Models for Ultra-High Granularity Particle Physics Detector Simulation: A Voyage From Emulation to Extrapolation](https://arxiv.org/abs/2403.13825) (2024)
@@ -2030,6 +2034,7 @@ This review was built with the help of the HEP-ML community, the [INSPIRE REST A
 
 ###  ML for theory
 
+* [Truth, beauty, and goodness in grand unification: a machine learning approach](https://arxiv.org/abs/2411.06718) (2024)
 * [cymyc -- Calabi-Yau Metrics, Yukawas, and Curvature](https://arxiv.org/abs/2410.19728) (2024)
 * [Calabi-Yau metrics through Grassmannian learning and Donaldson's algorithm](https://arxiv.org/abs/2410.11284) (2024)
 * [Bootstrapping string models with entanglement minimization and Machine-Learning](https://arxiv.org/abs/2409.18259) (2024)
@@ -2092,6 +2097,7 @@ This review was built with the help of the HEP-ML community, the [INSPIRE REST A
 
 ###  Searches and measurements where ML reconstruction is a core component
 
+* [Search for vector-like leptons coupling to first- and second-generation Standard Model leptons in $pp$ collisions at $\sqrt{s}](https://arxiv.org/abs/2411.07143) (2024)
 * [Observation of a rare beta decay of the charmed baryon with a Graph Neural Network](https://arxiv.org/abs/2410.13515) (2024)
 * [Search for light long-lived particles decaying to displaced jets in proton-proton collisions at $\sqrt{s}$](https://arxiv.org/abs/2409.10806) (2024)
 * [Accuracy versus precision in boosted top tagging with the ATLAS detector](https://arxiv.org/abs/2407.20127) [[DOI](https://doi.org/10.1088/1748-0221/19/08/P08018)] (2024)

docs/index.md

@@ -502,6 +502,7 @@ const expandElements = shouldExpand => {
 
     ####  BSM particles and models
 
+    * [Pseudo-observables and Deep Neural Network for mixed CP -- H to tau tau decays at LHC](https://arxiv.org/abs/2411.06216) (2024)
     * [Improving smuon searches with Neural Networks](https://arxiv.org/abs/2411.04526) (2024)
     * [Machine-Learning Analysis of Radiative Decays to Dark Matter at the LHC](https://arxiv.org/abs/2410.13799) (2024)
     * [Machine learning tagged boosted dark photon: A signature of fermionic portal matter at the LHC](https://arxiv.org/abs/2410.06925) (2024)
@@ -584,6 +585,7 @@ const expandElements = shouldExpand => {
 
     ####  Particle identification
 
+    * [Transformers for Charged Particle Track Reconstruction in High Energy Physics](https://arxiv.org/abs/2411.07149) (2024)
     * [Detecting highly collimated photon-jets from Higgs boson exotic decays with deep learning](https://arxiv.org/abs/2401.15690) (2024)
     * [Machine-learning-based particle identification with missing data](https://arxiv.org/abs/2401.01905) [[DOI](https://doi.org/10.1140/epjc/s10052-024-13047-3)] (2024)
     * [Study of residual artificial neural network for particle identification in the CEPC high-granularity calorimeter prototype](https://arxiv.org/abs/2310.09489) [[DOI](https://doi.org/10.1088/1748-0221/19/04/P04033)] (2023)
@@ -1128,6 +1130,7 @@ const expandElements = shouldExpand => {
     ###  Calibration
     </div>
 
+    * [Reweighting simulated events using machine-learning techniques in the CMS experiment](https://arxiv.org/abs/2411.03023) (2024)
     * [Vertex Imaging Hadron Calorimetry Using AI/ML Tools](https://arxiv.org/abs/2408.15385) (2024)
     * [ML-based Calibration and Control of the GlueX Central Drift Chamber](https://arxiv.org/abs/2403.13823) (2024)
     * [A Comparison of Deep Learning Models for Proton Background Rejection with the AMS Electromagnetic Calorimeter](https://arxiv.org/abs/2402.16285) (2024)
@@ -1600,6 +1603,7 @@ const expandElements = shouldExpand => {
     ###  (Variational) Autoencoders
     </div>
 
+    * [Fast multi-geometry calorimeter simulation with conditional self-attention variational autoencoders](https://arxiv.org/abs/2411.05996) (2024)
     * [CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation](https://arxiv.org/abs/2410.21611) (2024)
     * [Calo-VQ: Vector-Quantized Two-Stage Generative Model in Calorimeter Simulation](https://arxiv.org/abs/2405.06605) (2024)
     * [Deep Generative Models for Ultra-High Granularity Particle Physics Detector Simulation: A Voyage From Emulation to Extrapolation](https://arxiv.org/abs/2403.13825) (2024)
@@ -2267,6 +2271,7 @@ const expandElements = shouldExpand => {
     ###  ML for theory
     </div>
 
+    * [Truth, beauty, and goodness in grand unification: a machine learning approach](https://arxiv.org/abs/2411.06718) (2024)
     * [cymyc -- Calabi-Yau Metrics, Yukawas, and Curvature](https://arxiv.org/abs/2410.19728) (2024)
     * [Calabi-Yau metrics through Grassmannian learning and Donaldson's algorithm](https://arxiv.org/abs/2410.11284) (2024)
     * [Bootstrapping string models with entanglement minimization and Machine-Learning](https://arxiv.org/abs/2409.18259) (2024)
@@ -2339,6 +2344,7 @@ const expandElements = shouldExpand => {
     ###  Searches and measurements where ML reconstruction is a core component
     </div>
 
+    * [Search for vector-like leptons coupling to first- and second-generation Standard Model leptons in $pp$ collisions at $\sqrt{s}](https://arxiv.org/abs/2411.07143) (2024)
     * [Observation of a rare beta decay of the charmed baryon with a Graph Neural Network](https://arxiv.org/abs/2410.13515) (2024)
     * [Search for light long-lived particles decaying to displaced jets in proton-proton collisions at $\sqrt{s}$](https://arxiv.org/abs/2409.10806) (2024)
     * [Accuracy versus precision in boosted top tagging with the ATLAS detector](https://arxiv.org/abs/2407.20127) [[DOI](https://doi.org/10.1088/1748-0221/19/08/P08018)] (2024)

docs/recent.md

@@ -11,6 +11,12 @@ This is an automatically compiled list of papers which have been added to the li
 
 ## November 2024
 * [Improving smuon searches with Neural Networks](https://arxiv.org/abs/2411.04526) (2024)
+* [Pseudo-observables and Deep Neural Network for mixed CP -- H to tau tau decays at LHC](https://arxiv.org/abs/2411.06216) (2024)
+* [Truth, beauty, and goodness in grand unification: a machine learning approach](https://arxiv.org/abs/2411.06718) (2024)
+* [Reweighting simulated events using machine-learning techniques in the CMS experiment](https://arxiv.org/abs/2411.03023) (2024)
+* [Fast multi-geometry calorimeter simulation with conditional self-attention variational autoencoders](https://arxiv.org/abs/2411.05996) (2024)
+* [Transformers for Charged Particle Track Reconstruction in High Energy Physics](https://arxiv.org/abs/2411.07149) (2024)
+* [Search for vector-like leptons coupling to first- and second-generation Standard Model leptons in $pp$ collisions at $\sqrt{s}](https://arxiv.org/abs/2411.07143) (2024)
 * [Rejection Sampling with Autodifferentiation -- Case study: Fitting a Hadronization Model](https://arxiv.org/abs/2411.02194) (2024)
 * [The Fundamental Limit of Jet Tagging](https://arxiv.org/abs/2411.02628) (2024)
 * [Generative Unfolding with Distribution Mapping](https://arxiv.org/abs/2411.02495) (2024)

dump_bibtex_from_arxiv.py

@@ -89,7 +89,7 @@ def extract_arxiv_ids(input, output_file, replace_collab=True):
             if replace_collab:
                 bibtex = replace_collaboration_author(bibtex)
             # Write the date (in Mon day, year format) followed by BibTeX citation for each arxiv to the output file
-            f.write(f"% {date.strftime('%B %d, %Y')} \n{bibtex}\n")
+            f.write(f"% {date.strftime('%B %d, %Y')}* \n{bibtex}\n")
 
         print(f"{len(arxivs_dates)} citations written to {output_file} !")