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Paper Citation Record · LEDGER

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems

As of 19 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2505.12107.

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

pith.paper-citation-record.v1
2505.12107 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:50:16.591341Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T04:01:31.928056Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T21:51:31.096198Z

Reference resolution

43 of 43 outbound references displayed

  • verified exact0
  • verified fuzzy28
  • unresolved15
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ddded791-aa73-4f2c-86a6-84cabbc9d87c · outbound

This paper cites Principles of model checking.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Principles of model checking

Reference 1

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no resolver link, observed 2026-08-15T20:50:16.398956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0c620e0f-707c-4913-8535-b80ecd791b1d · outbound

This paper cites Data-driven statistical learning of temporal logic properties.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Data-driven statistical learning of temporal logic properties

Reference 2

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raw_fallback, observed 2026-08-15T20:50:17.189399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 006a3d7f-b902-4a3f-bf6b-d6b3cdefe672 · outbound

This paper cites Survey on mining signal temporal logic specifications.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Survey on mining signal temporal logic specifications

Reference 3

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raw_fallback, observed 2026-08-15T20:50:17.174474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e3c87bb6-22be-4dd0-9342-28883887db22 · outbound

This paper cites 40 years of formal methods - some obstacles and some possibilities? In FM , volume 8442 of Lecture Notes in Computer Science , pages 42--61.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems 40 years of formal methods - some obstacles and some possibilities? In FM , volume 8442 of Lecture Notes in Computer Science , pages 42--61

Reference 4

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no resolver link, observed 2026-08-15T20:50:16.412733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:50:16.412733Z digest=sha256:5c9fcc6e660a6a4a8306ddaac2b8fda799292b60f2d2581778d7849d914584d5

Observation bbe92c3f-f59c-4e76-88b8-6182d72fcce0 · outbound

This paper cites Explainable multi-agent reinforcement learning for temporal queries.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Explainable multi-agent reinforcement learning for temporal queries

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-15T20:50:17.150714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.417478Z digest=sha256:95a166078d54dd2761e9bfb8a3fe4f9fa56489ca196be85fa495cdf841db6e34

Observation 48b96bd6-6659-477f-97c4-e80587f49ea1 · outbound

This paper cites A decision tree approach to data classification using signal temporal logic.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems A decision tree approach to data classification using signal temporal logic

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-15T20:50:17.136291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 796a1d14-4be1-488c-abad-50e933c0ce66 · outbound

This paper cites Learning branching-time properties in CTL and ATL via constraint solving.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Learning branching-time properties in CTL and ATL via constraint solving

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-15T20:50:17.121348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.427001Z digest=sha256:4f1b2b8ea43e3d713c22c1f004cda8eb8c5e753449133ff631d74ac4dfce4f0a

Observation 8e175cc6-f920-4e42-9205-1d4f2f199083 · outbound

This paper cites Zavlanos, and Miroslav Pajic.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Zavlanos, and Miroslav Pajic

Reference 8

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raw_fallback, observed 2026-08-15T20:50:17.106630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.431232Z digest=sha256:e284234a34206a5d14623c5cdc7bf6e82f715f50158e5a908b0ad6be922cdf26

Observation faccf640-2ff4-47ac-852a-743bb80b824b · outbound

This paper cites OpenAI Gym.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems OpenAI Gym

Reference 10

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no resolver link, observed 2026-08-15T20:50:16.441105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:50:16.441105Z digest=sha256:584324f95c14c2b142e54cb3a27096668bf976226f6d3451c29f82293affd452

Observation 48d21668-aef0-466f-862f-0061b8dc7f0c · outbound

This paper cites McIlraith.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems McIlraith

Reference 11

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no resolver link, observed 2026-08-15T20:50:16.445627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:50:16.445627Z digest=sha256:d7e09262b3c9c733881aab30953f3321af03991cb3ebae980f3c78ad2bbe1f31

Observation 364c5710-385f-4af7-94f3-d0cb9153d91d · outbound

This paper cites Klassen, Richard Anthony Valenzano, and Sheila A.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Klassen, Richard Anthony Valenzano, and Sheila A

Reference 12

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raw_fallback, observed 2026-08-15T20:50:17.082524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.450492Z digest=sha256:a29f69d5065312ba7fa79b0a59cc0ee65229001daa8ba4fc5ad460c4b5bbc84b

Observation e8a3c952-2671-49ac-aba8-9ae1fe6767ff · outbound

This paper cites Learning temporal properties from event logs via sequential analysis.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Learning temporal properties from event logs via sequential analysis

Reference 13

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.455097Z digest=sha256:eacb11d2de5313b49c86f725d2d8ce3fe50c6ef0cd465fda397ce4cce0e07679

Observation 771edf46-ddad-4566-ad19-8bbe2775c55b · outbound

This paper cites Danesh, Anurag Koul, Alan Fern, and Saeed Khorram.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Danesh, Anurag Koul, Alan Fern, and Saeed Khorram

Reference 14

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raw_fallback, observed 2026-08-15T20:50:17.051529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.459533Z digest=sha256:032a88891d6745930b86ee1071446556e9d10699c34797c98ac3f4fd1624a6ea

Observation fe8d2b7a-7f8e-4100-b8ee-2c900dd8deed · outbound

This paper cites an unresolved cited work.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.463763Z digest=sha256:8f805bb3b844048a36694d567f8aee6d696fee82e75c48f99a51f9e7d96706b7

Observation 76124e97-7683-44b5-bcd4-d7885ba0b4e0 · outbound

This paper cites Spot’s temporal logic formulas, 2024.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Spot’s temporal logic formulas, 2024

Reference 16

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raw_fallback, observed 2026-08-15T20:50:17.021375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.467973Z digest=sha256:9a3df74e64b0d082c1ab8c12e40826244d6c1109d270d1d001cb62e7df38250e

Observation 9152a623-c2b7-4a55-bd9a-336aa72e4b51 · outbound

This paper cites Dwyer, George S.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Dwyer, George S

Reference 17

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raw_fallback, observed 2026-08-15T20:50:17.005952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.472165Z digest=sha256:4b5c33429a40f2bd9e7a0d5a4f0dca97384a5ca873cc1400c72562dcc43d2e7a

Observation a60532dd-83b7-4942-a498-bc82fb1be3ee · outbound

This paper cites A randomized protocol for signing contracts.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems A randomized protocol for signing contracts

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.991516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.476555Z digest=sha256:ef30bfa6bfdb0848471e1151a0ff17ad2753eda448079bfd73b1ff405cc108f7

Observation 433516d4-d163-40f0-8289-769adade1257 · outbound

This paper cites Analytic Combinatorics.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Analytic Combinatorics

Reference 19

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no resolver link, observed 2026-08-15T20:50:16.480804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:50:16.480804Z digest=sha256:21c3fe133acb545439bcc6ab5dd6dddd2280285a1e1e3c5986bfaa75ed398b8c

Observation 6003995f-d6e1-45ad-86bd-f9bee1ced33a · outbound

This paper cites NL2LTL - a python package for converting natural language (NL) instructions to linear temporal logic (LTL) formulas.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems NL2LTL - a python package for converting natural language (NL) instructions to linear temporal logic (LTL) formulas

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.967071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.485206Z digest=sha256:f4a4ae1ad8f87b1835190fbbd4f870a1c9f4000f417ab077b5f4b76aec133a64

Observation ccd71261-9ee9-4089-8107-25f3fe844ed8 · outbound

This paper cites Mark Gold.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Mark Gold

Reference 21

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unresolved
no resolver link, observed 2026-08-15T20:50:16.489344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:50:16.489344Z digest=sha256:76f4e73e2c35e3cfb2bc1da74649cf5952d39f5629c98a28c44985a21666e0b4

Observation 0a6ca280-c217-4b55-96bf-e15c4dcc8053 · outbound

This paper cites Pappas, and Insup Lee.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Pappas, and Insup Lee

Reference 22

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raw_fallback, observed 2026-08-15T20:50:16.943571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.493539Z digest=sha256:15581c764a55b6ea9b5d1651933cf31381ffa5aef51d2045bc980eb1064a316f

Observation c19fc5b9-b1ad-46dd-925a-8b44eacf763d · outbound

This paper cites Kemeny, J.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Kemeny, J

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.929141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.498090Z digest=sha256:a7082c84114e41829fd799c62f95c928b4c311a0eafdda83011769134439cfae

Observation c007fe94-80f9-47e8-aab3-eebef9689436 · outbound

This paper cites Kwiatkowska, Gethin Norman, and David Parker.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Kwiatkowska, Gethin Norman, and David Parker

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.914521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.502704Z digest=sha256:2ca733a06acb1e3748eed10e767a8ed6d7e1c5002bacefabf0d1800e5f61cfa3

Observation aa7eee67-78d6-4ac2-ac64-f94d2988f5e0 · outbound

This paper cites Reinforcement learning with temporal logic rewards.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Reinforcement learning with temporal logic rewards

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.898661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.507255Z digest=sha256:be1812040b027b1c3f760cd4cadcb56c59b4d3f767dfb655ecb9706fe11bd80c

Observation 22d8c51a-8e89-422b-87b4-6beb5f456e8d · outbound

This paper cites Bridging ltlf inference to GNN inference for learning ltlf formulae.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Bridging ltlf inference to GNN inference for learning ltlf formulae

Reference 26

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unresolved
no resolver link, observed 2026-08-15T20:50:16.511716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:50:16.511716Z digest=sha256:3a5549f3c598d4cf7883d26c3a9a8bc1fca965c51b471ea949425d873f035c8c

Observation 4df4799b-28df-4c70-b82b-d051208cb967 · outbound

This paper cites Explainable reinforcement learning: A survey and comparative review.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Explainable reinforcement learning: A survey and comparative review

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.873010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e3734175-1dc9-4cbf-b85a-bfbb2a7cd646 · outbound

This paper cites Deshmukh, Aniruddh Gopinath Puranic, Marcell Vazquez - Chanlatte, and Alexandre Donz \' e.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Deshmukh, Aniruddh Gopinath Puranic, Marcell Vazquez - Chanlatte, and Alexandre Donz \' e

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.858040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.520509Z digest=sha256:4048e56955caff13fa0a79f34be21a7376e4a82aa3b6f4cb2b146e5db7a8fb28

Observation 8114e611-f5d5-4851-b3da-28b57517855c · outbound

This paper cites Learning linear temporal properties.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Learning linear temporal properties

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.841582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.524839Z digest=sha256:c358c747b27c2005b2be52e9ede2482e43df7ee48009306a2857488789bf3d55

Observation 10fa1cab-b512-4bd9-b837-f97ca19de623 · outbound

This paper cites What is formal verification without specifications? A survey on mining LTL specifications.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems What is formal verification without specifications? A survey on mining LTL specifications

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.825582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.529221Z digest=sha256:f3e981865f398a8ab478b3c5c6936d3b33ed48973cc3f144b70e2394b49c04b4

Observation ab783ff3-cff8-4a84-aa19-ee332037a0d7 · outbound

This paper cites A robust genetic algorithm for learning temporal specifications from data.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems A robust genetic algorithm for learning temporal specifications from data

Reference 31

Resolution
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raw_fallback, observed 2026-08-15T20:50:16.811244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.533629Z digest=sha256:ff3cd1fde131bedbe90f3f2e6a77e3ef6cfc95ce49a72776bd64544423aec610

Observation e22927b1-b160-49d3-aba9-6140ef23f7b0 · outbound

This paper cites Norman and V.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Norman and V

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.796529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.537878Z digest=sha256:f8c9a1816f21039b94f99ad1540b085511cf26409e1fe3299926fe691652f77b

Observation 042a6e1d-cfa0-433f-8b25-0852a476510c · outbound

This paper cites The temporal logic of programs.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems The temporal logic of programs

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.781580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.542116Z digest=sha256:1730ad40ffbeb433e31215659240e6bb8577f9f11e1d8d657e3c21cf790482d7

Observation 429a84c4-b013-474f-94a4-dc0ac4be075a · outbound

This paper cites Sat-based learning of computation tree logic.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Sat-based learning of computation tree logic

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.767017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.546204Z digest=sha256:01a59e907e6ec85f93ae8f036be815f2fce3ab1ad838080f1af27dbd0d89eac3

Observation 64d90416-b23a-44e4-b930-0f4e96cf9c98 · outbound

This paper cites Scalable anytime algorithms for learning fragments of linear temporal logic.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Scalable anytime algorithms for learning fragments of linear temporal logic

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-15T20:50:16.550545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:50:16.550545Z digest=sha256:c78b28f01736617e6992197e9c3d82b6966310569ce4579650bae1b953f0527c

Observation 865bfb40-4d29-4c8e-a611-e4df2ab4525a · outbound

This paper cites Learning interpretable models in the property specification language.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Learning interpretable models in the property specification language

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T20:50:16.554936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:50:16.554936Z digest=sha256:78afbc58c50a867a97bdcafd9a00b9342c93437c93f2eecb444766c746264c63

Observation bc705b9a-4bcd-40ab-b145-80957d24b1e5 · outbound

This paper cites Learning Interpretable Temporal Properties from Positive Examples Only.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Learning Interpretable Temporal Properties from Positive Examples Only

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-15T20:50:16.559379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 384138f5-6909-4780-8206-32d83267f729 · outbound

This paper cites Specification: The biggest bottleneck in formal methods and autonomy.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Specification: The biggest bottleneck in formal methods and autonomy

Reference 38

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unresolved
no resolver link, observed 2026-08-15T20:50:16.563994Z

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source=arxiv_source observed=2026-08-15T20:50:16.563994Z digest=sha256:bfc76cb45de2cae5ee327e28d44274ddc46fbc91ba5f084eaf56b990ee98a7b2

Observation 5de8d508-3216-4080-a030-bd8135432fce · outbound

This paper cites Sample efficient model-free reinforcement learning from LTL specifications with optimality guarantees.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Sample efficient model-free reinforcement learning from LTL specifications with optimality guarantees

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.722553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0eb0989d-0edf-4d06-8751-e813ab76dc73 · outbound

This paper cites Generation of policy-level explanations for reinforcement learning.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Generation of policy-level explanations for reinforcement learning

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.708186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation cb621d53-85bb-4d8a-8de3-89c06471b8d2 · outbound

This paper cites Ltl learning on gpus.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Ltl learning on gpus

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:50:16.692759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 66aaaa61-b9cf-4c26-a26d-0d6fd75efbc2 · outbound

This paper cites an unresolved cited work.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-15T20:50:16.678403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T20:50:16.582618Z digest=sha256:3959d99cac9fd3c2dd1548a13e266bc1b105e8965e6f861b805d5e38dbe269a4

Observation d309d2d6-b745-4964-a434-b7554a777e65 · outbound

This paper cites End-to-end learning of ltlf formulae by faithful ltlf encoding.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems End-to-end learning of ltlf formulae by faithful ltlf encoding

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T20:50:16.586804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:50:16.586804Z digest=sha256:990d85c219c1c5bbd0bce31f0437973e24093633a8a66c16fcf4ab8700a35553

Observation b6e5d6b0-3ef6-4a98-81ce-31a53c5f16dd · outbound

This paper cites write newline.

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems write newline

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T20:50:16.591341Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T20:50:16.591341Z digest=sha256:b43d3f32563e0d53b9810ad3eb1815e04ddef62f7f5507041f8404e39a3ef02c

Pith citing papers

Observation 0c54ce1b-47bf-4469-9c71-459c3f21935e · inbound

SpecRLBench: A Benchmark for Generalization in Specification-Guided Reinforcement Learning cites this paper.

SpecRLBench: A Benchmark for Generalization in Specification-Guided Reinforcement Learning Learning Probabilistic Temporal Logic Specifications for Stochastic Systems

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:51:31.222364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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