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Paper Citation Record · LEDGER

Machine Learning in the 2HDM2S model for Dark Matter

As of 14 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 2 inbound Pith citation observations for arXiv:2509.01677.

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

pith.paper-citation-record.v1
2509.01677 v4

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-18T19:21:02.625794Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T12:51:49.155762Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-02T10:26:52.254140Z

Reference resolution

62 of 62 outbound references displayed

  • verified exact56
  • verified fuzzy4
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8a2f8b72-b22c-49cd-8a85-5134e065765e · outbound

This paper cites Planck 2013 results. I. Overview of products and scientific results.

Machine Learning in the 2HDM2S model for Dark Matter Planck 2013 results. I. Overview of products and scientific results

Reference 1

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local_arxiv, observed 2026-05-18T19:21:47.531865Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6369e422-df58-4689-9c9d-7f4ab2a93b18 · outbound

This paper cites Theory and phenomenology of two-Higgs-doublet models.

Machine Learning in the 2HDM2S model for Dark Matter Theory and phenomenology of two-Higgs-doublet models

Reference 2

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local_arxiv, observed 2026-05-18T19:21:47.515177Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 66b354f6-cc16-45e3-8042-4dd424394c4f · outbound

This paper cites The Anatomy of Electro-Weak Symmetry Breaking. II: The Higgs bosons in the Minimal Supersymmetric Model.

Machine Learning in the 2HDM2S model for Dark Matter The Anatomy of Electro-Weak Symmetry Breaking. II: The Higgs bosons in the Minimal Supersymmetric Model

Reference 3

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local_arxiv, observed 2026-05-18T19:21:47.491536Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f5576c2e-cc59-46c9-a750-856363f45664 · outbound

This paper cites an unresolved cited work.

Machine Learning in the 2HDM2S model for Dark Matter Unresolved cited work

Reference 4

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raw_fallback, observed 2026-05-18T19:22:50.079545Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation de6ee86c-bf48-4efe-901c-12cb7531f059 · outbound

This paper cites Dimopoulos, D.

Machine Learning in the 2HDM2S model for Dark Matter Dimopoulos, D

Reference 5

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raw_fallback, observed 2026-05-18T19:22:50.076557Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 27fe1a41-b243-49ef-9f81-e02c43663d13 · outbound

This paper cites Turning off the Lights: How Dark is Dark Matter?.

Machine Learning in the 2HDM2S model for Dark Matter Turning off the Lights: How Dark is Dark Matter?

Reference 6

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local_arxiv, observed 2026-05-18T19:21:47.537255Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f993eea2-d63d-4d8a-90e1-29ac4dd6e308 · outbound

This paper cites Particle Dark Matter: Evidence, Candidates and Constraints.

Machine Learning in the 2HDM2S model for Dark Matter Particle Dark Matter: Evidence, Candidates and Constraints

Reference 7

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local_arxiv, observed 2026-05-18T19:21:47.484970Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8a95e688-b8a6-4439-bd05-95b7dc65975a · outbound

This paper cites Dark Matter Candidates from Particle Physics and Methods of Detection.

Machine Learning in the 2HDM2S model for Dark Matter Dark Matter Candidates from Particle Physics and Methods of Detection

Reference 8

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local_arxiv, observed 2026-05-18T19:21:47.526363Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation dfc896a5-cc07-47ee-a18a-09962f3cd443 · outbound

This paper cites A Natural Two-Higgs-Doublet Model.

Machine Learning in the 2HDM2S model for Dark Matter A Natural Two-Higgs-Doublet Model

Reference 9

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local_arxiv, observed 2026-05-18T19:21:47.520938Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:afc64c042ccf92f3d587a3f44e0b59b43e66ebd921371c8b070ba86c7f7abf02

Observation 4733274f-e27b-494b-84d0-3eec69f3de0c · outbound

This paper cites Dark matter annihilation through a lepton-specific Higgs boson.

Machine Learning in the 2HDM2S model for Dark Matter Dark matter annihilation through a lepton-specific Higgs boson

Reference 10

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local_arxiv, observed 2026-05-18T19:21:47.503716Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 7033d933-32a7-49b6-a1ff-efa715ec5cb7 · outbound

This paper cites Direct and Indirect Singlet Scalar Dark Matter Detection in the Lepton-Specific two-Higgs-doublet Model.

Machine Learning in the 2HDM2S model for Dark Matter Direct and Indirect Singlet Scalar Dark Matter Detection in the Lepton-Specific two-Higgs-doublet Model

Reference 11

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local_arxiv, observed 2026-05-18T19:21:47.479527Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation fd44fa29-c9f5-4268-a45f-36dabcb3d9d2 · outbound

This paper cites Hints of Standard Model Higgs Boson at the LHC and Light Dark Matter Searches.

Machine Learning in the 2HDM2S model for Dark Matter Hints of Standard Model Higgs Boson at the LHC and Light Dark Matter Searches

Reference 12

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local_arxiv, observed 2026-05-18T19:21:47.497861Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 46b4a188-2719-4dd4-854e-5411c1816cc0 · outbound

This paper cites 2HDM Portal Dark Matter: LHC data and the Fermi-LAT 135 GeV Line.

Machine Learning in the 2HDM2S model for Dark Matter 2HDM Portal Dark Matter: LHC data and the Fermi-LAT 135 GeV Line

Reference 13

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local_arxiv, observed 2026-05-18T19:21:47.509721Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:7ca7229ceed2c5a70b35c04b7741e10a1e05a22a6b9eec32161240892d6cf6c0

Observation 42df37f9-1bca-41f1-9537-51cf019ee124 · outbound

This paper cites Extending two-Higgs-doublet models by a singlet scalar field - the Case for Dark Matter.

Machine Learning in the 2HDM2S model for Dark Matter Extending two-Higgs-doublet models by a singlet scalar field - the Case for Dark Matter

Reference 14

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local_arxiv, observed 2026-05-18T19:21:47.254565Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 823e426a-ffcb-4350-9eaf-bb38db359beb · outbound

This paper cites Implications of the observation of dark matter self-interactions for singlet scalar dark matter.

Machine Learning in the 2HDM2S model for Dark Matter Implications of the observation of dark matter self-interactions for singlet scalar dark matter

Reference 15

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arxiv_id, observed 2026-05-18T19:21:47.259431Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a6852d12-6536-44de-906e-a161a27541b5 · outbound

This paper cites The Next-to-Minimal Two Higgs Doublet Model.

Machine Learning in the 2HDM2S model for Dark Matter The Next-to-Minimal Two Higgs Doublet Model

Reference 16

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local_arxiv, observed 2026-05-18T19:21:47.370659Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 396362f9-c344-43e1-8b22-debb87bc2152 · outbound

This paper cites The N2HDM under Theoretical and Experimental Scrutiny.

Machine Learning in the 2HDM2S model for Dark Matter The N2HDM under Theoretical and Experimental Scrutiny

Reference 17

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arxiv_id, observed 2026-05-18T19:21:47.359392Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2276f10e-c912-44d7-a479-ff0c2c0a0067 · outbound

This paper cites Vacuum Instabilities in the N2HDM.

Machine Learning in the 2HDM2S model for Dark Matter Vacuum Instabilities in the N2HDM

Reference 18

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arxiv_id, observed 2026-05-18T19:21:47.354447Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f1119d42-5121-43d3-bd14-2821b9edd675 · outbound

This paper cites The Dark Phases of the N2HDM.

Machine Learning in the 2HDM2S model for Dark Matter The Dark Phases of the N2HDM

Reference 19

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arxiv_id, observed 2026-05-18T19:21:47.441818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6aea8e9c-1f82-485b-9795-bb02eef3e9e7 · outbound

This paper cites Electroweak Corrections to Dark Matter Direct Detection in the Dark Singlet Phase of the N2HDM.

Machine Learning in the 2HDM2S model for Dark Matter Electroweak Corrections to Dark Matter Direct Detection in the Dark Singlet Phase of the N2HDM

Reference 20

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arxiv_id, observed 2026-05-18T19:21:47.426328Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 259f3489-1eb0-4b74-89fa-1cc5e62725f2 · outbound

This paper cites Two Higgs Doublets and a Complex Singlet: Disentangling the Decay Topologies and Associated Phenomenology.

Machine Learning in the 2HDM2S model for Dark Matter Two Higgs Doublets and a Complex Singlet: Disentangling the Decay Topologies and Associated Phenomenology

Reference 21

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local_arxiv, observed 2026-05-18T19:21:47.249843Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f6c6b0d5-b7c0-46de-b9d9-6cde805efa65 · outbound

This paper cites A 96 GeV Higgs Boson in the 2HDM plus Singlet.

Machine Learning in the 2HDM2S model for Dark Matter A 96 GeV Higgs Boson in the 2HDM plus Singlet

Reference 22

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arxiv_id, observed 2026-05-18T19:21:47.338045Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 4872b809-8d7e-4b97-9d3d-c5ed2d704a5c · outbound

This paper cites Phenomenology of the dark matter sector in the 2HDM extended with complex scalar singlet.

Machine Learning in the 2HDM2S model for Dark Matter Phenomenology of the dark matter sector in the 2HDM extended with complex scalar singlet

Reference 23

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arxiv_id, observed 2026-05-18T19:21:47.283460Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:d21da5ab7d58ec6481613dfdd1b7c9a380885baf29f648c08a9b7fab79d20ce4

Observation f0ff0981-7df0-4e73-8199-9052908c887d · outbound

This paper cites Dark Matter Phenomenology in 2HDMS in light of the 95 GeV excess.

Machine Learning in the 2HDM2S model for Dark Matter Dark Matter Phenomenology in 2HDMS in light of the 95 GeV excess

Reference 24

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arxiv_id, observed 2026-05-18T19:21:47.421170Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:350ad8d16be85f95d30362b74fdaf50195893334c6b9d93aafa1b34c10a0d0dd

Observation 956f710a-cf3a-4f39-ab3f-6025798520d8 · outbound

This paper cites Vacuum (in)stability in 2HDMS vs N2HDM.

Machine Learning in the 2HDM2S model for Dark Matter Vacuum (in)stability in 2HDMS vs N2HDM

Reference 25

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arxiv_id, observed 2026-05-18T19:21:47.446983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 9cb7a5c0-a091-4a78-8b87-d07ab2e7de37 · outbound

This paper cites Dark Matter in Multi-Singlet Extensions of the Standard Model.

Machine Learning in the 2HDM2S model for Dark Matter Dark Matter in Multi-Singlet Extensions of the Standard Model

Reference 26

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arxiv_id, observed 2026-06-02T02:03:31.831305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:432bfbcf8e01067ebb63e5cc1f4a732a2cd30a4072620589580922aedae23055

Observation dee5521a-be7f-43fa-bc89-7cac44272833 · outbound

This paper cites The CP-conserving two-Higgs-doublet model: the approach to the decoupling limit.

Machine Learning in the 2HDM2S model for Dark Matter The CP-conserving two-Higgs-doublet model: the approach to the decoupling limit

Reference 27

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local_arxiv, observed 2026-05-18T19:21:47.468175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:0e36d9259a6664e0ffdd8b9cc2a32b6f121052c34c69e103b9a2702c9a406619

Observation d2e6b483-1974-4494-bd85-0d179061cbf2 · outbound

This paper cites Boundedness from below in the $U(1)\times U(1)$ three-Higgs-Doublet model.

Machine Learning in the 2HDM2S model for Dark Matter Boundedness from below in the $U(1)\times U(1)$ three-Higgs-Doublet model

Reference 28

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arxiv_id, observed 2026-05-18T19:21:47.431894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:2d38520b3fc421589da960d5d82e523542ca9db308277771dae38ab315bbe9a3

Observation 312ef783-ca9a-4670-9d94-c328d51f0f9d · outbound

This paper cites Alignment limit in three Higgs-doublet models.

Machine Learning in the 2HDM2S model for Dark Matter Alignment limit in three Higgs-doublet models

Reference 29

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arxiv_id, observed 2026-05-18T19:21:47.343091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:73076c7babf15bf254579a4f85049a9349e2a7513497a86f14a73e96d825fcf9

Observation e0c05602-b947-4e4f-86d8-882e318c2d6d · outbound

This paper cites an unresolved cited work.

Machine Learning in the 2HDM2S model for Dark Matter Unresolved cited work

Reference 30

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unresolved
raw_fallback, observed 2026-05-18T19:22:50.070787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:830064dfe48798352d17c04d97123ae4760e1e64428a464113ccad9d307b47ca

Observation 069435f5-16b8-4268-88c5-e760be592486 · outbound

This paper cites Vacuum Stability Conditions From Copositivity Criteria.

Machine Learning in the 2HDM2S model for Dark Matter Vacuum Stability Conditions From Copositivity Criteria

Reference 31

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local_arxiv, observed 2026-05-18T19:21:47.230779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:189dfa01a4150d978b38175623486490bb091a664e95c6bbafe68b041b303125

Observation afb4daa1-17e4-4f43-ac37-04aade11437b · outbound

This paper cites BFB conditions on a class of symmetry constrained 3HDM.

Machine Learning in the 2HDM2S model for Dark Matter BFB conditions on a class of symmetry constrained 3HDM

Reference 32

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arxiv_id, observed 2026-05-18T19:21:47.240086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:dfe509c28d09e18e7a734446bd2a2368565dd726ab2a4a0a37e75faf966ea9be

Observation b8aba86a-a47a-4864-b7c3-9f205ae6b08c · outbound

This paper cites Ping and F.

Machine Learning in the 2HDM2S model for Dark Matter Ping and F

Reference 33

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verified fuzzy
raw_fallback, observed 2026-05-18T19:22:50.073706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:2384a6f95053c944f6fa1c825ba4667e4b266de3d7ad5644fef920548c833bc3

Observation 8413759f-fd27-4106-a2f1-846c81c5b07a · outbound

This paper cites James and M.

Machine Learning in the 2HDM2S model for Dark Matter James and M

Reference 34

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verified fuzzy
raw_fallback, observed 2026-05-18T19:22:50.067583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:b998383e1af92ff681b8ff60c46598d2a4298e3d73d611e499bfc7a4a01a3e31

Observation 90089d8f-f240-4ae4-83c2-a7d89337c292 · outbound

This paper cites Multi-Higgs doublet models: physical parametrization, sum rules and unitarity bounds.

Machine Learning in the 2HDM2S model for Dark Matter Multi-Higgs doublet models: physical parametrization, sum rules and unitarity bounds

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-05-18T19:21:47.244585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:692e5ddae256774943a52639ce0eda7b5e485920f3f6d08163322597fef37b93

Observation 1e9e9260-ea9f-417d-998b-e930f48c0ca9 · outbound

This paper cites Unitarity bounds for all symmetry-constrained 3HDMs.

Machine Learning in the 2HDM2S model for Dark Matter Unitarity bounds for all symmetry-constrained 3HDMs

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.221000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:52cf01097e998b20cd8854326af0e7bb205807cbed988000a1c7b3dc9efce92b

Observation 14d8f421-dd7a-42e8-bca9-8d1cbb0e30a7 · outbound

This paper cites A precision constraint on multi-Higgs-doublet models.

Machine Learning in the 2HDM2S model for Dark Matter A precision constraint on multi-Higgs-doublet models

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-05-18T19:21:47.225877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:9b45e9b7fe163bcf63a2ad652334a22da717628c79c1ea18b9658af918cef9ff

Observation 188dedc7-ac53-4ada-a5c6-3e958aac5534 · outbound

This paper cites HiggsTools: BSM scalar phenomenology with new versions of HiggsBounds and HiggsSignals.

Machine Learning in the 2HDM2S model for Dark Matter HiggsTools: BSM scalar phenomenology with new versions of HiggsBounds and HiggsSignals

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.235445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:00cb54c3231660234db711bc95ea4f315d3fc489bc6fd7c3c48dda136a79e74d

Observation 20616549-f355-47ac-9f41-cda1a9efe126 · outbound

This paper cites micrOMEGAs 6.0: N-component dark matter.

Machine Learning in the 2HDM2S model for Dark Matter micrOMEGAs 6.0: N-component dark matter

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.399624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:577bf833fce70d4e39ad9e8c352e787d0b6656850522e2d50e780e757ce3a04b

Observation dfdb9816-17a8-458b-83f7-0de5893a5cbd · outbound

This paper cites Minimal semi-annihilating $\mathbb{Z}_N$ scalar dark matter.

Machine Learning in the 2HDM2S model for Dark Matter Minimal semi-annihilating $\mathbb{Z}_N$ scalar dark matter

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-05-18T19:21:47.473855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:42ea1f572e68da607f5c5126f65210a961c434bf7ec86adaf4a8e18b197e59d8

Observation 79f150d1-0ba5-477d-9ea6-7a6c18344548 · outbound

This paper cites Two dark matter candidates: the case of inert doublet and singlet scalars.

Machine Learning in the 2HDM2S model for Dark Matter Two dark matter candidates: the case of inert doublet and singlet scalars

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.296784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:1065d98d91baf68039a84a379902a4ffa7e928f9a7b2c220af56f4feca72d6d5

Observation f8e9cdc0-0fc0-47c7-b512-9f3f6c0cd89b · outbound

This paper cites A Precision Search for WIMPs with Charged Cosmic Rays.

Machine Learning in the 2HDM2S model for Dark Matter A Precision Search for WIMPs with Charged Cosmic Rays

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-05-18T19:21:47.389802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:5ec916f5d3ce8172d1467ce93dc424d22b95cf42834475578d4b7d552dc5b9db

Observation 8b07af24-664a-4508-9498-88bbf1cea678 · outbound

This paper cites Exploring Parameter Spaces with Artificial Intelligence and Machine Learning Black-Box Optimisation Algorithms.

Machine Learning in the 2HDM2S model for Dark Matter Exploring Parameter Spaces with Artificial Intelligence and Machine Learning Black-Box Optimisation Algorithms

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.302217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:90163ae5e75b89bac840eacda05beab986b45bf618bdc6a76b94629ab516cdae

Observation 7447101e-0dc2-4d2c-a121-17c5cd543c29 · outbound

This paper cites Combining Evolutionary Strategies and Novelty Detection to go Beyond the Alignment Limit of the $Z_3$ 3HDM.

Machine Learning in the 2HDM2S model for Dark Matter Combining Evolutionary Strategies and Novelty Detection to go Beyond the Alignment Limit of the $Z_3$ 3HDM

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.410173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:d85cf596a2633ebdff8bfb031eee66b96082c05021126ed6543de20d85ffae07

Observation 55677219-6f6a-46b8-8a2a-2ce8f5d2657e · outbound

This paper cites Unearthing large pseudoscalar Yukawa couplings with Machine Learning.

Machine Learning in the 2HDM2S model for Dark Matter Unearthing large pseudoscalar Yukawa couplings with Machine Learning

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.405046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:f81e723a97e4fbd8c9d382f6570a0cb433f2a1b73a818f22f79ffdd5221cacc8

Observation d78f9126-b62a-471f-8369-d20979566b63 · outbound

This paper cites Weak Radiative Decays of the B Meson and Bounds on $M_{H^\pm}$ in the Two-Higgs-Doublet Model.

Machine Learning in the 2HDM2S model for Dark Matter Weak Radiative Decays of the B Meson and Bounds on $M_{H^\pm}$ in the Two-Higgs-Doublet Model

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-05-18T19:21:47.451992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:a55cb323b4b83661d9ca08ef740c6c657d91a365a37c00456c34351a9e571c56

Observation d064de28-8c9b-4b93-a6f6-70427f6209ff · outbound

This paper cites de Souza, N.F.

Machine Learning in the 2HDM2S model for Dark Matter de Souza, N.F

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.326823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:991864bc6eef904818179d68d04281046dbfad1f311eeeb189809b781e9ca774

Observation 026b891e-6b5f-43a7-802b-59186f4a16c1 · outbound

This paper cites Constraining the Parameters of High-Dimensional Models with Active Learning.

Machine Learning in the 2HDM2S model for Dark Matter Constraining the Parameters of High-Dimensional Models with Active Learning

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.375886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:f25e3ce441b477c415ea3d016ac96caa53e5ea961cefc2cb14ab58ddc6f6d4dd

Observation c6766226-8f8d-4e65-9e52-e38d8370dc02 · outbound

This paper cites Efficient sampling of constrained high-dimensional theoretical spaces with machine learning.

Machine Learning in the 2HDM2S model for Dark Matter Efficient sampling of constrained high-dimensional theoretical spaces with machine learning

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.436963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:759bdf6834a75e78a317df82e91657f514f0398b547d6802773296f13274fcfa

Observation cdbee315-cab8-4b31-b7fb-14e41b65531f · outbound

This paper cites Active learning BSM parameter spaces.

Machine Learning in the 2HDM2S model for Dark Matter Active learning BSM parameter spaces

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.380349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:b397c70a1b6960389243cfe6de6731364034b71871e8bef49f69b6cde9da2ebe

Observation 65768ebd-a104-4d9a-b3d1-e85aa0a1d299 · outbound

This paper cites Bayesian active search on parameter space: A 95 GeV spin-0 resonance in the (B−L)SSM.

Machine Learning in the 2HDM2S model for Dark Matter Bayesian active search on parameter space: A 95 GeV spin-0 resonance in the (B−L)SSM

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.308530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:ccc94ac77a4e5f769bc6f5ee3c29a13016660c2f22f2b2cae66303c81b04b355

Observation f71502b6-c23c-488f-93f9-a51bda525b86 · outbound

This paper cites Constraining the 3HDM Parameter Space using Active Learning.

Machine Learning in the 2HDM2S model for Dark Matter Constraining the 3HDM Parameter Space using Active Learning

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.394545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:6a557a6200c441f8c188cba3ff8b474623e57b8586778cedaf75d23ebb5c5431

Observation 3cd01750-1ddd-4a16-9bd7-fdc3345dd675 · outbound

This paper cites Hammad, R.

Machine Learning in the 2HDM2S model for Dark Matter Hammad, R

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.415549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:ef23c1ce062a11e4a8a655f87ac6bf72410ba71d81e06837d7126c5fe5e65fec

Observation e1c640f9-8ff1-4662-902e-1f7c14fba828 · outbound

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

Machine Learning in the 2HDM2S model for Dark Matter A Living Review of Machine Learning for Particle Physics

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.321016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:166cec12bff8314734efa2f9cdd4e1de2e71b3921cd3feac99a4ae354be5e256

Observation 23e04b94-eaae-4099-ac84-d464077acc90 · outbound

This paper cites Modern Machine Learning for LHC Physicists.

Machine Learning in the 2HDM2S model for Dark Matter Modern Machine Learning for LHC Physicists

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.314819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:83ccd63b220855fec8fc33896ab4763e7fbbf2fe2cfc798cf384deb61cb0ea4e

Observation a55715d0-15ad-4db0-ab0c-71ed7f7a49da · outbound

This paper cites Hansen and A.

Machine Learning in the 2HDM2S model for Dark Matter Hansen and A

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T19:22:50.064065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:80c84cb565983e57b1c741346bdb14e75f54e31865c21332685dd7757f804137

Observation 8dfd2577-07b5-4f42-b190-cadc8bdabe87 · outbound

This paper cites The CMA Evolution Strategy: A Tutorial.

Machine Learning in the 2HDM2S model for Dark Matter The CMA Evolution Strategy: A Tutorial

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-05-18T19:21:47.385099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:133ed2f5568559e964be4a083dc7fe7d014b4ee7a0cc1e10ab07f3d628fda1fd

Observation 5fc90a1d-53e7-4d50-acb7-a89799ad6b26 · outbound

This paper cites Fog on the horizon: a new definition of the neutrino floor for direct dark matter searches.

Machine Learning in the 2HDM2S model for Dark Matter Fog on the horizon: a new definition of the neutrino floor for direct dark matter searches

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.462803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:1e60100e51da9357f234de7a17f4f7da49ce7d2d154e878cfa8d46e1048e9afd

Observation b35b69e7-d0a2-4e4a-84df-e5217a70ef1c · outbound

This paper cites Dark Matter vs. Neutrinos: The effect of astrophysical uncertainties and timing information on the neutrino floor.

Machine Learning in the 2HDM2S model for Dark Matter Dark Matter vs. Neutrinos: The effect of astrophysical uncertainties and timing information on the neutrino floor

Reference 59

Resolution
verified exact
local_arxiv, observed 2026-05-18T19:21:47.457208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:4eb098e64f9300507d6c0f67590e4ab898ac2d4f6e752fd233720a7f89f01fea

Observation e5a8fcf1-11a0-4272-9fed-5c0a08725d1b · outbound

This paper cites Casting a Wide Signal Net with Future Direct Dark Matter Detection Experiments.

Machine Learning in the 2HDM2S model for Dark Matter Casting a Wide Signal Net with Future Direct Dark Matter Detection Experiments

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-05-18T19:21:47.364991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:157ce1b27caa8b3c49eeff76ce4685aa261937ec16ab17c66e213290ad9f1468

Observation 3d86753e-32ae-458e-858a-8c89d8350b84 · outbound

This paper cites Beyond the Veil: Charting WIMP Territories at the Neutrino Floor.

Machine Learning in the 2HDM2S model for Dark Matter Beyond the Veil: Charting WIMP Territories at the Neutrino Floor

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.331881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:da3563ad5bbd4aa80802c67eb10352cca1d43b4a4c6666192a3315932ce85640

Observation 96d8a2ce-52aa-4766-8556-ba44242d5d44 · outbound

This paper cites CYGNUS: Feasibility of a nuclear recoil observatory with directional sensitivity to dark matter and neutrinos.

Machine Learning in the 2HDM2S model for Dark Matter CYGNUS: Feasibility of a nuclear recoil observatory with directional sensitivity to dark matter and neutrinos

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.349029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:21:02.625794Z digest=sha256:1f9229b7d086e47f03923b78fb90c90de6f843fbfc2caf9518a96fb3dc185ca3

Pith citing papers

Observation 2fbfdb84-5529-4033-9a32-cf1631effc8c · inbound

Perturbative unitarity for models with singlet and doublet scalars cites this paper.

Perturbative unitarity for models with singlet and doublet scalars Machine Learning in the 2HDM2S model for Dark Matter

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-04T12:51:49.155762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:51:49.155762Z digest=sha256:d4858564af35a6bfb8a617844f2b9699c02f45d657b4c790e10ff0768664ecaa

Observation c7d38b12-a9cc-4515-8db8-0c744f465f7c · inbound

BSMArt 2: simpler and faster parameter space scans cites this paper.

BSMArt 2: simpler and faster parameter space scans Machine Learning in the 2HDM2S model for Dark Matter

Reference 93

Resolution
verified exact
local_arxiv, observed 2026-07-02T10:26:52.255378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T05:02:44.747731Z digest=sha256:e2acd9a40cd207c4af153dc97492d08d106a9b2a2554764a9c8fcd7208154da7