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Paper Citation Record · LEDGER

A Step Toward Interpretability: Smearing the Likelihood

As of 12 August 2026, this Paper Citation Record lists 100 of 121 outbound references and 1 inbound Pith citation observation for arXiv:2501.07643.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.07643 v2

Coverage vector

measured 100 of 121 reference resolution

Typed states for the displayed outbound observations.

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One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-11T01:54:10.924145Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T04:10:58.569494Z

Reference resolution

100 of 121 outbound references displayed

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External citation measurements

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Outbound references

Observation 3d0e17c7-d9f6-40ac-a890-dd011a46024f · outbound

This paper cites Jet Substructure at the Large Hadron Collider: A Review of Recent Advances in Theory and Machine Learning.

A Step Toward Interpretability: Smearing the Likelihood Jet Substructure at the Large Hadron Collider: A Review of Recent Advances in Theory and Machine Learning

Reference 1

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Observation 2b4145ed-deef-409c-8892-34f717b5ae87 · outbound

This paper cites Jet Substructure at the Large Hadron Collider: Experimental Review.

A Step Toward Interpretability: Smearing the Likelihood Jet Substructure at the Large Hadron Collider: Experimental Review

Reference 2

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Observation 30c67854-f1e9-4893-a2f7-1331f80f5809 · outbound

This paper cites Deep Learning and its Application to LHC Physics.

A Step Toward Interpretability: Smearing the Likelihood Deep Learning and its Application to LHC Physics

Reference 3

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This paper cites Machine Learning in High Energy Physics Community White Paper.

A Step Toward Interpretability: Smearing the Likelihood Machine Learning in High Energy Physics Community White Paper

Reference 4

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Observation 64cc2222-7ec5-4605-8642-e4a40a95b250 · outbound

This paper cites Radovic, M.

A Step Toward Interpretability: Smearing the Likelihood Radovic, M

Reference 5

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Observation c1835af4-6e9d-407e-bb3d-78a6ed453753 · outbound

This paper cites Machine learning and the physical sciences.

A Step Toward Interpretability: Smearing the Likelihood Machine learning and the physical sciences

Reference 6

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Observation 899fe640-2e4f-4636-994a-b6fcc6e087cc · outbound

This paper cites Machine and Deep Learning Applications in Particle Physics.

A Step Toward Interpretability: Smearing the Likelihood Machine and Deep Learning Applications in Particle Physics

Reference 7

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Observation ffc72319-3966-4b58-8c73-e91cc7a5619b · outbound

This paper cites Modern Machine Learning and Particle Physics.

A Step Toward Interpretability: Smearing the Likelihood Modern Machine Learning and Particle Physics

Reference 8

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Observation 6821fb0a-88df-4d38-9cd6-1bddbe791c3f · outbound

This paper cites Machine Learning in the Search for New Fundamental Physics.

A Step Toward Interpretability: Smearing the Likelihood Machine Learning in the Search for New Fundamental Physics

Reference 9

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Observation adfc61c9-9c89-4a76-809f-135978e9d341 · outbound

This paper cites Machine Learning in Nuclear Physics.

A Step Toward Interpretability: Smearing the Likelihood Machine Learning in Nuclear Physics

Reference 10

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Observation bac524b2-9924-4c88-9a45-c1957270ec56 · outbound

This paper cites Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning.

A Step Toward Interpretability: Smearing the Likelihood Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning

Reference 11

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Observation 131721c1-7b9a-4c61-83af-9177f3b26d2e · outbound

This paper cites Modern Machine Learning for LHC Physicists.

A Step Toward Interpretability: Smearing the Likelihood Modern Machine Learning for LHC Physicists

Reference 12

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Observation 0b7eb7ed-267a-4c66-bfd2-bf896482dd39 · outbound

This paper cites Jets and Jet Substructure at Future Colliders.

A Step Toward Interpretability: Smearing the Likelihood Jets and Jet Substructure at Future Colliders

Reference 13

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Observation 8d3f1ec9-6c23-4878-93d0-d4b9901caeef · outbound

This paper cites DeZoort, P.

A Step Toward Interpretability: Smearing the Likelihood DeZoort, P

Reference 14

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Observation a5cd6349-d930-4a7a-9930-a2b78171539c · outbound

This paper cites Exploring QCD matter in extreme conditions with Machine Learning.

A Step Toward Interpretability: Smearing the Likelihood Exploring QCD matter in extreme conditions with Machine Learning

Reference 15

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This paper cites Machine Learning for Anomaly Detection in Particle Physics.

A Step Toward Interpretability: Smearing the Likelihood Machine Learning for Anomaly Detection in Particle Physics

Reference 16

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Observation 607dcba8-1390-44ba-b850-7f4f772d4c1b · outbound

This paper cites Machine Learning in High Energy Physics: A review of heavy-flavor jet tagging at the LHC.

A Step Toward Interpretability: Smearing the Likelihood Machine Learning in High Energy Physics: A review of heavy-flavor jet tagging at the LHC

Reference 17

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Observation 6c33ab55-0704-4fdb-8752-436fc3d2b807 · outbound

This paper cites A Living Review of Machine Learning for Particle Physics.

A Step Toward Interpretability: Smearing the Likelihood A Living Review of Machine Learning for Particle Physics

Reference 18

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Observation 26b67e8f-bc77-43f1-ad19-989c6f38b79f · outbound

This paper cites QCD Masterclass Lectures on Jet Physics and Machine Learning.

A Step Toward Interpretability: Smearing the Likelihood QCD Masterclass Lectures on Jet Physics and Machine Learning

Reference 19

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Observation e8fa577b-904e-4e41-b357-81a8d4d445b5 · outbound

This paper cites TASI Lectures on Physics for Machine Learning.

A Step Toward Interpretability: Smearing the Likelihood TASI Lectures on Physics for Machine Learning

Reference 20

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This paper cites Rudin, Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead, Nature machine intelligence 1 (2019), no.

A Step Toward Interpretability: Smearing the Likelihood Rudin, Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead, Nature machine intelligence 1 (2019), no

Reference 21

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Observation b131c6c5-b5ae-4acf-a4ab-2f0da8e2f09e · outbound

This paper cites Molnar, Interpretable machine learning.

A Step Toward Interpretability: Smearing the Likelihood Molnar, Interpretable machine learning

Reference 22

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This paper cites Interpretable machine learning in Physics.

A Step Toward Interpretability: Smearing the Likelihood Interpretable machine learning in Physics

Reference 23

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A Step Toward Interpretability: Smearing the Likelihood Interpretable machine learning for particle physics

Reference 24

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This paper cites 10,000 einsteins: Ai and the future of theoretical physics.

A Step Toward Interpretability: Smearing the Likelihood 10,000 einsteins: Ai and the future of theoretical physics

Reference 25

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A Step Toward Interpretability: Smearing the Likelihood Unresolved cited work

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A Step Toward Interpretability: Smearing the Likelihood Unresolved cited work

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A Step Toward Interpretability: Smearing the Likelihood What is the Machine Learning?

Reference 28

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A Step Toward Interpretability: Smearing the Likelihood Opening the black box of neural nets: case studies in stop/top discrimination

Reference 29

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A Step Toward Interpretability: Smearing the Likelihood Mapping Machine-Learned Physics into a Human-Readable Space

Reference 30

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A Step Toward Interpretability: Smearing the Likelihood Resurrecting $b\bar{b}h$ with kinematic shapes

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A Step Toward Interpretability: Smearing the Likelihood Feature Selection with Distance Correlation

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A Step Toward Interpretability: Smearing the Likelihood Boosted top tagging and its interpretation using Shapley values

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A Step Toward Interpretability: Smearing the Likelihood Retrieval of Boost Invariant Symbolic Observables via Feature Importance

Reference 34

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A Step Toward Interpretability: Smearing the Likelihood Boosted Top Tagging through Flavour-violating interactions at the LHC

Reference 35

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A Step Toward Interpretability: Smearing the Likelihood Improved Precision in $Vh(\rightarrow b\bar b)$ via Boosted Decision Trees

Reference 36

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A Step Toward Interpretability: Smearing the Likelihood Interplay of Traditional Methods and Machine Learning Algorithms for Tagging Boosted Objects

Reference 37

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A Step Toward Interpretability: Smearing the Likelihood Neyman and E

Reference 38

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A Step Toward Interpretability: Smearing the Likelihood Unresolved cited work

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Observation 9d4cf294-6fef-4e27-83c8-bef04f032fa8 · outbound

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A Step Toward Interpretability: Smearing the Likelihood Kinoshita, Mass singularities of Feynman amplitudes , J

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Observation 76cab4ce-a95a-4880-8ae7-ccdca831f22c · outbound

This paper cites an unresolved cited work.

A Step Toward Interpretability: Smearing the Likelihood Unresolved cited work

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Observation bd8a5561-4ae1-4121-a3ae-2694dbbff97b · outbound

This paper cites an unresolved cited work.

A Step Toward Interpretability: Smearing the Likelihood Unresolved cited work

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Observation e163f3fc-aaf3-4830-947a-5ab94808b241 · outbound

This paper cites The Metric Space of Collider Events.

A Step Toward Interpretability: Smearing the Likelihood The Metric Space of Collider Events

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Observation b2e9f7f3-1f11-405f-bf95-5c45a5d4d1c0 · outbound

This paper cites Does SUSY have friends? A new approach for LHC event analysis.

A Step Toward Interpretability: Smearing the Likelihood Does SUSY have friends? A new approach for LHC event analysis

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Observation 7d325ba3-3a71-4d7f-87c1-0e161e935e7f · outbound

This paper cites Use of a Generalized Energy Mover's Distance in the Search for Rare Phenomena at Colliders.

A Step Toward Interpretability: Smearing the Likelihood Use of a Generalized Energy Mover's Distance in the Search for Rare Phenomena at Colliders

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Observation e5103f80-1daa-4d8f-b40b-4924011e8e50 · outbound

This paper cites Linearized Optimal Transport for Collider Events.

A Step Toward Interpretability: Smearing the Likelihood Linearized Optimal Transport for Collider Events

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Observation f4116303-d192-4b9b-b683-b65b0fda6cc2 · outbound

This paper cites Covariantizing Phase Space.

A Step Toward Interpretability: Smearing the Likelihood Covariantizing Phase Space

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Observation a219c415-7553-478f-94cc-5cc8f6820b35 · outbound

This paper cites Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance.

A Step Toward Interpretability: Smearing the Likelihood Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance

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Observation c4f2e289-4848-43fe-9d90-9696c5c6c06b · outbound

This paper cites Which Metric on the Space of Collider Events?.

A Step Toward Interpretability: Smearing the Likelihood Which Metric on the Space of Collider Events?

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Observation 09277fcc-db09-4aaf-9445-969bda85cb35 · outbound

This paper cites Finding NEEMo: Geometric Fitting using Neural Estimation of the Energy Mover's Distance.

A Step Toward Interpretability: Smearing the Likelihood Finding NEEMo: Geometric Fitting using Neural Estimation of the Energy Mover's Distance

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Observation 226cf8a4-c046-465c-b980-64985260e778 · outbound

This paper cites Pileup and Infrared Radiation Annihilation (PIRANHA): A Paradigm for Continuous Jet Grooming.

A Step Toward Interpretability: Smearing the Likelihood Pileup and Infrared Radiation Annihilation (PIRANHA): A Paradigm for Continuous Jet Grooming

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source=pdf_text observed=2026-08-10T20:44:15.671998Z digest=sha256:3d9cf7af49aa356c69951d26fcb0109524ed72f2bea719662805828956d7408a

Observation f4040678-7f30-4782-9020-ad59e6e54a1d · outbound

This paper cites A Spectral Metric for Collider Geometry.

A Step Toward Interpretability: Smearing the Likelihood A Spectral Metric for Collider Geometry

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Observation a9ecb741-49b0-4d5a-a076-9fd62803bb5e · outbound

This paper cites Earth mover's distance as a measure of CP violation.

A Step Toward Interpretability: Smearing the Likelihood Earth mover's distance as a measure of CP violation

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Observation 91190134-b8b8-49d5-8908-56079e48ffa2 · outbound

This paper cites SHAPER: Can You Hear the Shape of a Jet?.

A Step Toward Interpretability: Smearing the Likelihood SHAPER: Can You Hear the Shape of a Jet?

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Observation ac4ca19e-e87c-4be4-8528-9d55182e5d9b · outbound

This paper cites Exploring Optimal Transport for Event-Level Anomaly Detection at the Large Hadron Collider.

A Step Toward Interpretability: Smearing the Likelihood Exploring Optimal Transport for Event-Level Anomaly Detection at the Large Hadron Collider

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Observation 062f2c49-a2a3-4ad0-8f92-8328e975c410 · outbound

This paper cites The Phase Space Distance Between Collider Events.

A Step Toward Interpretability: Smearing the Likelihood The Phase Space Distance Between Collider Events

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Observation f882c555-ab63-4049-8aab-bc9cee41b90b · outbound

This paper cites SPECTER: Efficient Evaluation of the Spectral EMD.

A Step Toward Interpretability: Smearing the Likelihood SPECTER: Efficient Evaluation of the Spectral EMD

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source=pdf_text observed=2026-08-10T20:44:15.699001Z digest=sha256:c80793e8e6d6a9742b5834f0e8bca7ed7a5aa6a748978a4f81a0b9298c2d7fe2

Observation 73e252f6-e4dd-44ed-8ee8-eef59b177d30 · outbound

This paper cites How Much Information is in a Jet?.

A Step Toward Interpretability: Smearing the Likelihood How Much Information is in a Jet?

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Observation 92a571a1-6e38-4db0-9f34-0ea01f9a3b5c · outbound

This paper cites A Theory of Quark vs. Gluon Discrimination.

A Step Toward Interpretability: Smearing the Likelihood A Theory of Quark vs. Gluon Discrimination

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Observation 9ffee29c-0df5-494f-9eea-b621fe526884 · outbound

This paper cites Towards Machine Learning Analytics for Jet Substructure.

A Step Toward Interpretability: Smearing the Likelihood Towards Machine Learning Analytics for Jet Substructure

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Observation 80f2844d-530d-4873-b244-45e1e6f84bcb · outbound

This paper cites Rosenblat, Remarks on some nonparametric estimates of a density function , Ann.

A Step Toward Interpretability: Smearing the Likelihood Rosenblat, Remarks on some nonparametric estimates of a density function , Ann

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Observation add51a8c-5aac-4201-9cfc-9c0dfbe75fde · outbound

This paper cites Parzen, On estimation of a probability density function and mode , The annals of mathematical statistics 33 (1962), no.

A Step Toward Interpretability: Smearing the Likelihood Parzen, On estimation of a probability density function and mode , The annals of mathematical statistics 33 (1962), no

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Observation bc6e630a-d07c-4220-ad98-22d366b3feb7 · outbound

This paper cites Ahmad and G.

A Step Toward Interpretability: Smearing the Likelihood Ahmad and G

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Observation c48ab269-a67c-4a38-8e84-c0d01a9a7ae1 · outbound

This paper cites Cohn and G.

A Step Toward Interpretability: Smearing the Likelihood Cohn and G

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Observation c6d18379-fc6c-4476-afc9-d181df348499 · outbound

This paper cites Deep Learning Scaling is Predictable, Empirically.

A Step Toward Interpretability: Smearing the Likelihood Deep Learning Scaling is Predictable, Empirically

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Observation d4eafe80-a09e-43a7-ad77-76c5c0b0eff7 · outbound

This paper cites Scaling Laws for Neural Language Models.

A Step Toward Interpretability: Smearing the Likelihood Scaling Laws for Neural Language Models

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Observation 299a4adb-d0a6-4f80-b81f-40d3cbae3583 · outbound

This paper cites A Constructive Prediction of the Generalization Error Across Scales.

A Step Toward Interpretability: Smearing the Likelihood A Constructive Prediction of the Generalization Error Across Scales

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Observation b21e2e53-7279-4767-9026-529c02bf36ae · outbound

This paper cites Scaling Laws for Autoregressive Generative Modeling.

A Step Toward Interpretability: Smearing the Likelihood Scaling Laws for Autoregressive Generative Modeling

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Observation a1d5df66-cdf5-481a-8c4e-668f1752c57a · outbound

This paper cites an unresolved cited work.

A Step Toward Interpretability: Smearing the Likelihood Unresolved cited work

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Observation b61c1466-069a-4d7f-a1aa-8b29101cfe7f · outbound

This paper cites Fr´ echet,Sur la loi de probabilit´ e de l’´ ecart maximum, Ann.

A Step Toward Interpretability: Smearing the Likelihood Fr´ echet,Sur la loi de probabilit´ e de l’´ ecart maximum, Ann

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Observation aaa30af5-f42e-471a-92b2-13fca0541c1c · outbound

This paper cites an unresolved cited work.

A Step Toward Interpretability: Smearing the Likelihood Unresolved cited work

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Observation a2600b29-231b-4745-92b0-e4a5c43efd08 · outbound

This paper cites Von Mises, La distribution de la plus grande de n valuers , Rev.

A Step Toward Interpretability: Smearing the Likelihood Von Mises, La distribution de la plus grande de n valuers , Rev

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Observation 4c92f18b-fa4d-447f-8327-ea96f4357b86 · outbound

This paper cites Gnedenko, Sur la distribution limite du terme maximum d’une serie aleatoire , Annals of mathematics 44 (1943), no.

A Step Toward Interpretability: Smearing the Likelihood Gnedenko, Sur la distribution limite du terme maximum d’une serie aleatoire , Annals of mathematics 44 (1943), no

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source=pdf_text observed=2026-08-10T20:44:15.767988Z digest=sha256:ea56ee3f076bd04349e0b6640583b146b7ebbeb2077616f104e184c88f71e50c

Observation 0291b699-c87b-49d4-b14c-852e15f286de · outbound

This paper cites The Fundamental Limit of Jet Tagging.

A Step Toward Interpretability: Smearing the Likelihood The Fundamental Limit of Jet Tagging

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Observation e20309b6-9b6c-408c-8302-8873c949bda7 · outbound

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A Step Toward Interpretability: Smearing the Likelihood Fukushima, Visual feature extraction by a multilayered network of analog threshold elements, IEEE Transactions on Systems Science and Cybernetics 5 (1969), no

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Observation 7f7a792d-9cf9-4d22-ac6f-1609810d145e · outbound

This paper cites an unresolved cited work.

A Step Toward Interpretability: Smearing the Likelihood Unresolved cited work

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Observation 55dceec3-1fab-4655-8706-6bf548b1b3e8 · outbound

This paper cites Fodor, How to See the Differences Between Quark and Gluon Jets , Phys.

A Step Toward Interpretability: Smearing the Likelihood Fodor, How to See the Differences Between Quark and Gluon Jets , Phys

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Observation 54e57d24-feb8-454e-95f7-1ffd4a8d55f2 · outbound

This paper cites Lonnblad, C.

A Step Toward Interpretability: Smearing the Likelihood Lonnblad, C

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Observation 11118c50-d85b-4e28-8e03-9e389fecf7f9 · outbound

This paper cites Lonnblad, C.

A Step Toward Interpretability: Smearing the Likelihood Lonnblad, C

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Observation d6b2fa2f-29de-433d-a296-c0ee2f845218 · outbound

This paper cites Csabai, F.

A Step Toward Interpretability: Smearing the Likelihood Csabai, F

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Observation eb5971a8-34e9-46c4-b328-56d611273757 · outbound

This paper cites Jones, TOWARDS A SYSTEMATIC JET CLASSIFICATION , Phys.

A Step Toward Interpretability: Smearing the Likelihood Jones, TOWARDS A SYSTEMATIC JET CLASSIFICATION , Phys

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Observation d638e14b-f7d0-4c24-9a07-25b5170fb849 · outbound

This paper cites Pumplin, How to tell quark jets from gluon jets , Phys.

A Step Toward Interpretability: Smearing the Likelihood Pumplin, How to tell quark jets from gluon jets , Phys

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A Step Toward Interpretability: Smearing the Likelihood Unresolved cited work

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Observation e48f5f5b-c8da-4a86-99cc-fdd3daf6bc0e · outbound

This paper cites Private communication.

A Step Toward Interpretability: Smearing the Likelihood Private communication

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This paper cites Casimir Meets Poisson: Improved Quark/Gluon Discrimination with Counting Observables.

A Step Toward Interpretability: Smearing the Likelihood Casimir Meets Poisson: Improved Quark/Gluon Discrimination with Counting Observables

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This paper cites Systematic Quark/Gluon Identification with Ratios of Likelihoods.

A Step Toward Interpretability: Smearing the Likelihood Systematic Quark/Gluon Identification with Ratios of Likelihoods

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Observation 1c7f9abb-8559-4a7f-ac56-6ebb5820718f · outbound

This paper cites The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations.

A Step Toward Interpretability: Smearing the Likelihood The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations

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This paper cites A comprehensive guide to the physics and usage of PYTHIA 8.3.

A Step Toward Interpretability: Smearing the Likelihood A comprehensive guide to the physics and usage of PYTHIA 8.3

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This paper cites The anti-k_t jet clustering algorithm.

A Step Toward Interpretability: Smearing the Likelihood The anti-k_t jet clustering algorithm

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Observation a5dc8dce-f51b-45f6-a15f-087cd2d1e182 · outbound

This paper cites FastJet user manual.

A Step Toward Interpretability: Smearing the Likelihood FastJet user manual

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Observation 87ee0d90-d73b-45c1-8614-f9bad726ec21 · outbound

This paper cites Catani, Y.

A Step Toward Interpretability: Smearing the Likelihood Catani, Y

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Observation 009fe684-36e0-4d76-83ad-cdf745ea2920 · outbound

This paper cites Successive Combination Jet Algorithm For Hadron Collisions.

A Step Toward Interpretability: Smearing the Likelihood Successive Combination Jet Algorithm For Hadron Collisions

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Observation 0ed56e87-6103-4ab0-b8fe-81feaf5211f9 · outbound

This paper cites Systematics of quark/gluon tagging.

A Step Toward Interpretability: Smearing the Likelihood Systematics of quark/gluon tagging

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Observation 04f6c3c1-6003-4fd4-be58-4eccaf979481 · outbound

This paper cites Infrared safe definition of jet flavour.

A Step Toward Interpretability: Smearing the Likelihood Infrared safe definition of jet flavour

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Observation c5abfdf8-4b00-4e90-bb69-f2e6cb4306c8 · outbound

This paper cites Practical Jet Flavour Through NNLO.

A Step Toward Interpretability: Smearing the Likelihood Practical Jet Flavour Through NNLO

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Observation 955c5d56-1570-4bd7-a536-49f24227f7d9 · outbound

This paper cites A Fragmentation Approach to Jet Flavor.

A Step Toward Interpretability: Smearing the Likelihood A Fragmentation Approach to Jet Flavor

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Observation 59d6af11-0d17-4e37-95c5-47a7cd010a75 · outbound

This paper cites Infrared-safe flavoured anti-$k_T$ jets.

A Step Toward Interpretability: Smearing the Likelihood Infrared-safe flavoured anti-$k_T$ jets

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Observation e78c2b13-48d6-4d63-a60f-8c75d8278b29 · outbound

This paper cites A dress of flavour to suit any jet.

A Step Toward Interpretability: Smearing the Likelihood A dress of flavour to suit any jet

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Observation 78be1476-a41e-4e0f-bbda-139e9fd8d4dd · outbound

This paper cites Flavoured jets with exact anti-$k_t$ kinematics and tests of infrared and collinear safety.

A Step Toward Interpretability: Smearing the Likelihood Flavoured jets with exact anti-$k_t$ kinematics and tests of infrared and collinear safety

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Observation e2e9b0b2-ce85-406e-967d-5e889f02af6c · outbound

This paper cites Hadron masses and power corrections to event shapes.

A Step Toward Interpretability: Smearing the Likelihood Hadron masses and power corrections to event shapes

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Pith citing papers

Observation 7efc7dd0-9348-4ddd-80f1-476128bb60cc · inbound

Testing machine-learned distributions against Monte Carlo data for the QCD chiral phase transition cites this paper.

Testing machine-learned distributions against Monte Carlo data for the QCD chiral phase transition A Step Toward Interpretability: Smearing the Likelihood

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