Paper Citation Record · LEDGER

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands

As of 10 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2501.12353.

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

pith.paper-citation-record.v1
2501.12353 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:18:53.957752Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:45:46.018628Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:45:46.127821Z

Reference resolution

15 of 15 outbound references displayed

verified exact1
verified fuzzy13
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 01b46306-e5b1-4c90-b4ef-0d21d5d644c1 · outbound

This paper cites Integrated sensing and communications: Recent advances and ten open challenges,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Integrated sensing and communications: Recent advances and ten open challenges,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T17:18:53.770663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 800659a3-1ea7-4a1c-a041-6977e48b4d5b · outbound

This paper cites Performance analysis of near-field isac based on an accurate channel model,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Performance analysis of near-field isac based on an accurate channel model,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.172332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aaf5c1b4-83c0-4487-9987-22c65ed127cf · outbound

This paper cites Inte- grated sensing and communications: Background and applications,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Inte- grated sensing and communications: Background and applications,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.159004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8ec02279-92af-4cf3-a234-e9ef2e8b48bd · outbound

This paper cites Hybrid deep reinforcement learning for enhancing localization and communication efficiency in ris-aided cooperative isac systems,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Hybrid deep reinforcement learning for enhancing localization and communication efficiency in ris-aided cooperative isac systems,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.146536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation edfc7b25-e123-40f9-9cca-f96aae4a2930 · outbound

This paper cites Bayesian learning for double-ris aided isac systems with superimposed pilots and data,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Bayesian learning for double-ris aided isac systems with superimposed pilots and data,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.134341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c1bb27b6-36fb-4a39-b0c1-fc780e7bf106 · outbound

This paper cites Target sensing with intelligent reflecting surface: Architecture and performance,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Target sensing with intelligent reflecting surface: Architecture and performance,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.121579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bfb47558-0d82-4d3e-acd4-a127e64d49df · outbound

This paper cites Crb minimization for ris-aided mmwave integrated sensing and communi- cations,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Crb minimization for ris-aided mmwave integrated sensing and communi- cations,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.109868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d7ab4d8e-edd8-4883-9043-0f73caefff5a · outbound

This paper cites Intelligent reflecting surface aided wireless sensing: Applications and design issues,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Intelligent reflecting surface aided wireless sensing: Applications and design issues,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.097905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6073b861-4c75-4a86-a977-3c77d41f33c9 · outbound

This paper cites Joint channel and direction estimation for ground-to-uav communications enabled by a simultaneous reflecting and sensing ris,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Joint channel and direction estimation for ground-to-uav communications enabled by a simultaneous reflecting and sensing ris,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.085120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 38ab1850-b814-4905-a232-b41284e23a07 · outbound

This paper cites Target-mounted intelligent reflecting surface for secure wireless sensing,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Target-mounted intelligent reflecting surface for secure wireless sensing,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.072203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 978b1392-04e6-44f8-9eaa-6a6de72991d6 · outbound

This paper cites Joint beamforming design for hybrid ris-assisted mmwave isac system relying on hybrid precoding structure,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Joint beamforming design for hybrid ris-assisted mmwave isac system relying on hybrid precoding structure,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.059058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 71972350-1895-4b70-b26d-c4ab65e6cca6 · outbound

This paper cites En- ergy efficient user clustering, hybrid precoding and power optimization in terahertz mimo-noma systems,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands En- ergy efficient user clustering, hybrid precoding and power optimization in terahertz mimo-noma systems,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.045177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4c776085-caa9-483d-933b-b040a2b2c1f4 · outbound

This paper cites Performance evaluation of thz wireless systems operating in 275-400 ghz band,.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Performance evaluation of thz wireless systems operating in 275-400 ghz band,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.029617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1b025f31-59a8-4a57-a39b-ca1ead456302 · outbound

This paper cites Active RIS vs. Passive RIS: Which Will Prevail in 6G?.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Active RIS vs. Passive RIS: Which Will Prevail in 6G?

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-10T17:18:53.997169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 816af57c-f50e-4774-ada2-22370a9968b0 · outbound

This paper cites Eaves and E.

Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands Eaves and E

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:18:54.013661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation 5238f3ff-ce3b-48c6-b8d7-790d0a2c9162 · inbound

Foundation Model-Aided Deep Reinforcement Learning for RIS-Assisted Wireless Communication cites this paper.

Foundation Model-Aided Deep Reinforcement Learning for RIS-Assisted Wireless Communication Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:45:46.132641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.