add Panda paper

HEPML.bib

@@ -1,5 +1,15 @@
 # HEPML Papers
 
+% December 1, 2025
+@article{Young:2025qbx,
+    author = "Young, Samuel and Terao, Kazuhiro",
+    title = "{Panda: Self-distillation of Reusable Sensor-level Representations for High Energy Physics}",
+    eprint = "2512.01324",
+    archivePrefix = "arXiv",
+    primaryClass = "hep-ex",
+    month = "12",
+    year = "2025"
+}
 
 % November 11, 2025
 @article{Gavranovic:2025wcj,

HEPML.tex

@@ -193,7 +193,7 @@
 	\end{itemize}
 \item \textbf{Anomaly detection}~\cite{Liu:2025kfw,Gerlach:2025brx,CMS:2025lmn,DAvanzo:2025tkf,Arguin:2025lyr,Hallin:2025wyc,Boggia:2025fjj,Ragoni:2025mju,ATLAS:2025cdi,Cheng:2025qhg,Vaselli:2025zkl,ClarkeHall:2025oiz,Dillon:2025yqe,Araz:2025oax,Puljak:2025gtj,Cheng:2025ewj,deSouza:2025riy,ATLAS:2025kuz,Hou:2025prp,Brennan:2025fqy,Chekanov:2025xpk,Banda:2025nrv,Chen:2025mxf,Klein:2025lbj,Chowdhury:2025mul,Oleksiyuk:2025pmu,Metzger:2025ecl,Gambhir:2025afb,ATLAS:2025obc,Brinkerhoff:2025rob,Khot:2025kqg,Arguin:2025ewq,CMS:2024nsz,Hammad:2024dsn,Das:2024fwo,DARWIN:2024unx,Duarte:2024lsg,Zhang:2024ebl,Chekanov:2024ezm,Matos:2024ggs,Caron:2024zxk,Harilal:2024tqq,Leigh:2024chm,Grosso:2024nho,Li:2024htp,Cheng:2024yig,Oleksiyuk:2024hru,Krause:2023uww,Sengupta:2023vtm,Zipper:2023ybp,Metodiev:2023izu,Liu:2023djx,Zhang:2023khv,Bai:2023yyy,Grosso:2023owo,Freytsis:2023cjr,Buhmann:2023acn,Finke:2023ltw,Bickendorf:2023nej,CMSECAL:2023fvz,Chekanov:2023uot,ATLAS:2023azi,Vaslin:2023lig,Golling:2023yjq,Mikuni:2023tok,Sengupta:2023xqy,Golling:2023juz,Roche:2023int,Schuhmacher:2023pro,Mastandrea:2022vas,Araz:2022zxk,Kasieczka:2022naq,Hallin:2022eoq,Kamenik:2022qxs,Park:2022zov,Caron:2022wrw,Dillon:2022mkq,Verheyen:2022tov,Finke:2022lsu,Fanelli:2022xwl,Letizia:2022xbe,Raine:2022hht,Birman:2022xzu,Dillon:2022tmm,Jiang:2022sfw,Alvi:2022fkk,Buss:2022lxw,Aguilar-Saavedra:2022ejy,Bradshaw:2022qev,Ngairangbam:2021yma,Canelli:2021aps,dAgnolo:2021aun,Chekanov:2021pus,Mikuni:2021nwn,Lester:2021aks,Tombs:2021wae,Aguilar-Saavedra:2021utu,Herrero-Garcia:2021goa,Jawahar:2021vyu,Fraser:2021lxm,Ostdiek:2021bem,Hallin:2021wme,Govorkova:2021utb,Volkovich:2021txe,Kasieczka:2021tew,Govorkova:2021hqu,Caron:2021wmq,Dorigo:2021iyy,Aarrestad:2021oeb,Kahn:2021drv,Atkinson:2021nlt,Shih:2021kbt,Finke:2021sdf,Dillon:2021nxw,Collins:2021nxn,Bortolato:2021zic,Blance:2021gcs,Batson:2021agz,Chakravarti:2021svb,Kasieczka:2021xcg,Stein:2020rou,Faroughy:2020gas,Park:2020pak,vanBeekveld:2020txa,Mikuni:2020qds,pol2020anomaly,1815227,aguilarsaavedra2020mass,Alexander:2020mbx,Thaprasop:2020mzp,Khosa:2020qrz,Cheng:2020dal,Amram:2020ykb,1800445,1797846,collaboration2020dijet,knapp2020adversarially,Romao:2020ojy,Romao:2019dvs,Aguilar-Saavedra:2017rzt,Nachman:2020lpy,Andreassen:2020nkr,Dillon:2019cqt,1809.02977,Mullin:2019mmh,DeSimone:2018efk,Hajer:2018kqm,Blance:2019ibf,Cerri:2018anq,Roy:2019jae,Heimel:2018mkt,Farina:2018fyg,DAgnolo:2019vbw,Collins:2019jip,Collins:2018epr,DAgnolo:2018cun}
 \\\textit{The goal of anomaly detection is to identify abnormal events.  The abnormal events could be from physics beyond the Standard Model or from faults in a detector.  While nearly all searches for new physics are technically anomaly detection, this category is for methods that are mode-independent (broadly defined).  Anomalies in high energy physics tend to manifest as over-densities in phase space (often called `population anomalies') in contrast to off-manifold anomalies where you can flag individual examples as anomalous. }
-\item \textbf{Foundation Models, LLMs}~\cite{Bhimji:2025isp,Song:2025odk,Morales-Alvarado:2025isx,Bakshi:2025fgx,Visive:2025flm,Hallin:2025ywf,Diefenbacher:2025zzn,Sagar:2025mrd,Li:2025vvr,McGreivy:2025rrz,Sagar:2025ebh,Park:2025ebs,Barman:2025kqr,Algren:2025zff,Saqlain:2025owc,Heneka:2025fpe,Giroux:2025elr,Tani:2025osu,Mikuni:2025tar,Barman:2025wfb,Amram:2024fjg,Ho:2024qyf,OmanaKuttan:2024mwr,Wildridge:2024yeg,Leigh:2024ked,Mikuni:2024qsr,Zhang:2024kws,Fanelli:2024ktq,Harris:2024sra,Birk:2024knn,Vigl:2024lat}
+\item \textbf{Foundation Models, LLMs}~\cite{Young:2025qbx,Bhimji:2025isp,Song:2025odk,Morales-Alvarado:2025isx,Bakshi:2025fgx,Visive:2025flm,Hallin:2025ywf,Diefenbacher:2025zzn,Sagar:2025mrd,Li:2025vvr,McGreivy:2025rrz,Sagar:2025ebh,Park:2025ebs,Barman:2025kqr,Algren:2025zff,Saqlain:2025owc,Heneka:2025fpe,Giroux:2025elr,Tani:2025osu,Mikuni:2025tar,Barman:2025wfb,Amram:2024fjg,Ho:2024qyf,OmanaKuttan:2024mwr,Wildridge:2024yeg,Leigh:2024ked,Mikuni:2024qsr,Zhang:2024kws,Fanelli:2024ktq,Harris:2024sra,Birk:2024knn,Vigl:2024lat}
   \\\textit{A foundation model is a machine learning or deep learning model that is trained on broad data such that it can be applied across a wide range of use cases.}
 \item \textbf{Kolmogorov-Arnold Networks (KANs)}~\cite{Dai:2025dir,Kou:2024hzd,Abasov:2024hyq,Erdmann:2024unt}
   \\\textit{Kolmogorov-Arnold Networks (KANs) are alternatives to standard multi-layer perceptrons in which instead of fixed activation functions on nodes (``neurons'') have learnable activation functions on edges (``weights''). This makes them more expressible and interpretable compared to multi-layer perceptrons.}

README.md

@@ -2356,6 +2356,7 @@ This review was built with the help of the HEP-ML community, the [INSPIRE REST A
 
 ##  Foundation Models, LLMs.
 
+* [Panda: Self-distillation of Reusable Sensor-level Representations for High Energy Physics](https://arxiv.org/abs/2512.01324) (2025)
 * [OmniLearned: A Foundation Model Framework for All Tasks Involving Jet Physics](https://arxiv.org/abs/2510.24066) (2025)
 * [Iterated Agent for Symbolic Regression](https://arxiv.org/abs/2510.08317) (2025)
 * [Foundation models for equation discovery in high energy physics](https://arxiv.org/abs/2510.03397) (2025)

docs/index.md

@@ -2543,6 +2543,7 @@ const expandElements = shouldExpand => {
 
 ??? example "Foundation Models, LLMs."
 
+    * [Panda: Self-distillation of Reusable Sensor-level Representations for High Energy Physics](https://arxiv.org/abs/2512.01324) (2025)
     * [OmniLearned: A Foundation Model Framework for All Tasks Involving Jet Physics](https://arxiv.org/abs/2510.24066) (2025)
     * [Iterated Agent for Symbolic Regression](https://arxiv.org/abs/2510.08317) (2025)
     * [Foundation models for equation discovery in high energy physics](https://arxiv.org/abs/2510.03397) (2025)