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Paper Citation Record · LEDGER

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints

As of 15 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.07136.

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

pith.paper-citation-record.v1
2607.07136 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-09T19:27:20.046253Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

  • verified exact4
  • verified fuzzy27
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6d7f5f3f-84cd-4365-9d53-f3ed7ef08580 · outbound

This paper cites Lipschitz Continuity of Signal Temporal Logic Robustness Measures: Synthesizing Control Barrier Functions from One Expert Demonstration.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Lipschitz Continuity of Signal Temporal Logic Robustness Measures: Synthesizing Control Barrier Functions from One Expert Demonstration

Reference 1

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verified exact
local_arxiv, observed 2026-07-09T19:36:29.273756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 65990dcd-5550-4e79-9275-6e129d4d1756 · outbound

This paper cites Control barrier functions: Theory and applications.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Control barrier functions: Theory and applications

Reference 2

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.443834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e0d561d8-1cbf-4b87-86d6-85c133d9c411 · outbound

This paper cites Spatiotemporal tubes for temporal reach-avoid-stay tasks in unknown systems.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Spatiotemporal tubes for temporal reach-avoid-stay tasks in unknown systems

Reference 3

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.445577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e96b2090-16a5-4ec1-a8a6-cd8d760d71c4 · outbound

This paper cites Approximation-free control for signal temporal logic specifications using spatiotemporal tubes.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Approximation-free control for signal temporal logic specifications using spatiotemporal tubes

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.440430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:d02216eb865611bed16664ba3cbbca8f3230912603c233d5166833c3639f55b9

Observation 1f8f3fda-0935-4e51-9811-0fca271421c4 · outbound

This paper cites Control barrier functions for the full class of signal temporal logic tasks using spatiotemporal tubes.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Control barrier functions for the full class of signal temporal logic tasks using spatiotemporal tubes

Reference 5

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verified exact
arxiv_id, observed 2026-07-09T19:36:29.267754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 1cb0dc1b-39df-4011-ad6d-8d9d2a49cac3 · outbound

This paper cites Approximation-free control of unknown euler-lagrangian systems under input constraints.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Approximation-free control of unknown euler-lagrangian systems under input constraints

Reference 6

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verified exact
arxiv_id, observed 2026-07-09T19:36:29.277007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:a1c8df4fcb5a85c75d794eff1b9c0dd7f47802f872bb7dd8971d87ddcef2d0c5

Observation b37b5efe-470d-4642-bc02-9f642d5d8f98 · outbound

This paper cites Robust satisfaction of temporal logic over real-valued signals.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Robust satisfaction of temporal logic over real-valued signals

Reference 7

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.480878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 221ec9f2-a179-492c-8d34-a8335d77ea93 · outbound

This paper cites Signal temporal logic compliant co-design of planning and control.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Signal temporal logic compliant co-design of planning and control

Reference 8

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.461204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:874bf2373dd879db292c540484af15489e3acb7eb4620ad8268ce3542f6203a4

Observation a51f7546-e650-4ae9-9668-f209c787e873 · outbound

This paper cites Backpropagation through signal temporal logic specifica- tions: Infusing logical structure into gradient-based methods.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Backpropagation through signal temporal logic specifica- tions: Infusing logical structure into gradient-based methods

Reference 9

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.482662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 055c82c5-2b33-405d-88af-f20ae089371f · outbound

This paper cites Real-time RRT* with signal temporal logic preferences.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Real-time RRT* with signal temporal logic preferences

Reference 10

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.450672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e25228f1-33ad-485d-972d-5a0e280f1644 · outbound

This paper cites Control barrier functions for signal temporal logic tasks.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Control barrier functions for signal temporal logic tasks

Reference 11

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.484414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:26334bf6174b437dfb01c5b7fac2326d83f88c6057c7f4481b2dcbbac24e88be

Observation a5fbc112-2862-4c26-9a0c-a1d54111f113 · outbound

This paper cites Funnel control for fully actuated systems under a fragment of signal temporal logic specifications.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Funnel control for fully actuated systems under a fragment of signal temporal logic specifications

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.462952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:fef46003ea773491a16b17e5e769c3afe0233a14d0e1456d83469f2be4303bc1

Observation 8a58e650-5b85-4f7f-a9c8-3c7653455e67 · outbound

This paper cites Prescribed performance control for signal temporal logic specifications.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Prescribed performance control for signal temporal logic specifications

Reference 13

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.475367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:a131f6099bc1cfc6e6e151b00abd0fe66b700f38a0a597bfee2a040e97f6caab

Observation 08ca1090-8bfe-4f96-946c-6a2f1732fd24 · outbound

This paper cites Compositional synthesis of signal temporal logic tasks via assume-guarantee contracts.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Compositional synthesis of signal temporal logic tasks via assume-guarantee contracts

Reference 14

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.477162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:d3d12a9c1fcb35ca5b1b923acc289fa0c8e05612f16f85ba0896e9c874f8a4e7

Observation 14a235ad-8f1a-4cb4-96e6-9cd37eb54418 · outbound

This paper cites Recurrent neural network controllers for signal temporal logic specifications subject to safety constraints.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Recurrent neural network controllers for signal temporal logic specifications subject to safety constraints

Reference 15

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.471845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:dd305aee4528cb96a5cf3b7b67d6b289e32d0f25f8756a18619bb4c149b459f5

Observation 09ccfeca-f79f-4475-8b91-6c8348d9d6f7 · outbound

This paper cites Safe model-based control from signal temporal logic specifica- tions using recurrent neural networks.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Safe model-based control from signal temporal logic specifica- tions using recurrent neural networks

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.449040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:fcebcc2d3bb61c879f5173808ced66baa9f179d9f265c83072e30899036603dd

Observation 0dca3e01-66b4-46da-9385-547cfda8ed4e · outbound

This paper cites Learning robust and correct controllers from signal temporal logic specifications using barriernet.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Learning robust and correct controllers from signal temporal logic specifications using barriernet

Reference 17

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.442168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:186fd4e3ec860b1aaaa6595b46c44989dee09c178aba846739ba24816ed92572

Observation 9352bfbf-288c-46ba-9b9c-be29d5ee1f36 · outbound

This paper cites Monitoring temporal properties of continuous signals.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Monitoring temporal properties of continuous signals

Reference 18

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.466372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:81a3f9ed7cabc7e6e97093fe3f76d767d33a9cec2fb47cde8f2e5d36c771af35

Observation 5413137f-fef2-4fe4-9557-b1fd49f9250d · outbound

This paper cites Robot control by using only joint position measurements.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Robot control by using only joint position measurements

Reference 19

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.468244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:b6f7e80cae954caffc5fcfd1d74bb29f91fb56d153380fcd54d50141c13e2b93

Observation 26593616-cb21-4105-ace3-e4db0b77c9a4 · outbound

This paper cites Euler-Lagrange systems.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Euler-Lagrange systems

Reference 20

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.473558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:ffe677ee5bf088aff902efc7951816a6ef8c825ae8ce2d4901307acdced7c671

Observation 58538ea4-9905-4795-b9ea-9a3889bf3159 · outbound

This paper cites An improved artificial potential field method for path planning and formation control of the multi-UA V systems.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints An improved artificial potential field method for path planning and formation control of the multi-UA V systems

Reference 21

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verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.479021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:4c897fdcc33607de90dc12bfe42c6d843f01af92f32564b6c522b59f7b106d3a

Observation 76fc0452-1b95-438a-a847-ceb94e762183 · outbound

This paper cites Learning from demonstrations using signal temporal logic.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Learning from demonstrations using signal temporal logic

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.464636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:544dcf388809e7971136083e1601ee4f39cfa8872605ad26fde21d386e6cd27d

Observation ea1ec35f-c0d0-4910-80f4-c3108ec5ff29 · outbound

This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.457529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:f73a02060028099ed97d6f810f16433c5791eb1f616471699f9fe93651055d3e

Observation e6edca5b-e530-4e06-b3d4-e92df450a913 · outbound

This paper cites Model predictive control with signal temporal logic specifications.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Model predictive control with signal temporal logic specifications

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.438648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:0cbff0847fc896ca0a01d50318b54d0fc9f622ec59299b31e70d4fa5f54f40ca

Observation 7d79479f-43cb-41e4-935d-f2616cfac014 · outbound

This paper cites Reactive synthesis from signal temporal logic specifications.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Reactive synthesis from signal temporal logic specifications

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.486179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:f60d445d7251b120a598d2cb12872f0604e148b04134614202dc43e0deedf91c

Observation 7f795e53-f940-4b59-baeb-a74e6b64c579 · outbound

This paper cites An overview of gradient descent optimization algorithms.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints An overview of gradient descent optimization algorithms

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-07-09T19:36:29.270837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:e343c43611e3c0650923a9999f384c4762811005a126f7aded7f8d128445b1c1

Observation 63d674f2-2d78-4c3e-bad3-273dae8bf9c5 · outbound

This paper cites Funnel-based reward shaping for signal temporal logic tasks in reinforcement learning.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Funnel-based reward shaping for signal temporal logic tasks in reinforcement learning

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.470039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:8ae8fa18d89043e2abab63f02ee44d889b78a7a8e5a7a192f6e63df37b40528f

Observation 3d0ab773-ecac-4447-8727-d2878d6c5e47 · outbound

This paper cites Accelerated training of physics-informed neural networks (pinns) using meshless discretizations.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Accelerated training of physics-informed neural networks (pinns) using meshless discretizations

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.447309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:94096cea17d48f7aff9d4d4bd512333ee68f8ad515c4c6a0402f76f4dea66d41

Observation 4915e258-c76b-4a7a-98df-667ec12abe39 · outbound

This paper cites Robotics: Modelling, Planning and Control.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Robotics: Modelling, Planning and Control

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.455380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:953e45753bd5f0975aeeef0596497554d92d3c102f667444c06077be1fa275a6

Observation bfe6d674-8431-44ce-9d68-1b6569aa2a7f · outbound

This paper cites Multi-agent motion planning from signal temporal logic specifications.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints Multi-agent motion planning from signal temporal logic specifications

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.459492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:119852cede48909d682797e96ccc94c1ec2837bc134fb71f80805fbd7d87101a

Observation 0f3f4dfc-a516-444f-968f-5202629f8367 · outbound

This paper cites V erification and control of hybrid systems: a symbolic approach.

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints V erification and control of hybrid systems: a symbolic approach

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T19:36:29.488170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T19:27:20.046253Z digest=sha256:c7eb15e7e098a86515942a9f2b41f3c0b7c6cb3a3c16cc2bd0a82cb4c8b0a8d0

Pith citing papers

No inbound Pith citation observations are available.