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Paper Citation Record · LEDGER

Partial Label Learning for Automated Theorem Proving

As of 8 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2507.03314.

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

pith.paper-citation-record.v1
2507.03314 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:18:26.884619Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

36 of 36 outbound references displayed

  • verified exact7
  • verified fuzzy13
  • unresolved9
  • parse uncertain0
  • malformed identifier3
  • metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0ab9164b-b937-4cbe-92d8-d2134781b916 · outbound

This paper cites Premise selection for mathematics by corpus analysis and kernel methods.

Partial Label Learning for Automated Theorem Proving Premise selection for mathematics by corpus analysis and kernel methods

Reference 1

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no resolver link, observed 2026-08-06T20:18:22.749496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:18:22.749496Z digest=sha256:2e5a45c46de6903d859d6ae2cfcabd8ce9bb6a5bbc1c264348d5124d348e226f

Observation bb67d249-60ea-42f1-9370-0084be648cca · outbound

This paper cites Alemi, Fran c ois Chollet, Niklas Een, Geoffrey Irving, Christian Szegedy, and Josef Urban.

Partial Label Learning for Automated Theorem Proving Alemi, Fran c ois Chollet, Niklas Een, Geoffrey Irving, Christian Szegedy, and Josef Urban

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:22.798590Z digest=sha256:f0dd0af1080dbd174d94ff55bc89cbe3fa4e14dc003f839b8b1a42edaf5b1e90

Observation 70044e2c-7e90-4888-9f41-7bf4f15ba29c · outbound

This paper cites Thinking fast and slow with deep learning and tree search.

Partial Label Learning for Automated Theorem Proving Thinking fast and slow with deep learning and tree search

Reference 3

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raw_fallback, observed 2026-08-06T20:18:33.103791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:22.901507Z digest=sha256:9661130cf94b38bc37f6d8491df4d42f03bc1c845e564da0539520b20fef5c67

Observation 7b403128-1d46-4860-968c-f79c5135df77 · outbound

This paper cites Thinking Fast and Slow with Deep Learning and Tree Search.

Partial Label Learning for Automated Theorem Proving Thinking Fast and Slow with Deep Learning and Tree Search

Reference 4

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no resolver link, observed 2026-08-06T20:18:23.091803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:18:23.091803Z digest=sha256:b7b61e3536d04f4410f4d714e7f9ff6925703ab6fab2d52eb6088c90ce5b2f9d

Observation c0882c5c-1528-4269-b0aa-6d3e195fb24b · outbound

This paper cites Lucas, Peter I.

Partial Label Learning for Automated Theorem Proving Lucas, Peter I

Reference 5

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raw_fallback, observed 2026-08-06T20:18:32.877156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:23.221471Z digest=sha256:e7a660ac5a42d902a0649a8faa9d15289a9bd3ea185dad62baec28665f5f9111

Observation dc92c6ae-0495-4b7b-a448-27ccc88a8bca · outbound

This paper cites XGBoost : A scalable tree boosting system.

Partial Label Learning for Automated Theorem Proving XGBoost : A scalable tree boosting system

Reference 6

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no resolver link, observed 2026-08-06T20:18:23.321383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:18:23.321383Z digest=sha256:3b431db66db60cbfdf00b7bb3e1412ac8e24f619291d45f82968bcb85ad00a16

Observation 25eca343-190e-4165-be2e-12e9da9c9f61 · outbound

This paper cites Learning from partial labels.

Partial Label Learning for Automated Theorem Proving Learning from partial labels

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:23.517382Z digest=sha256:b862ed49b0c30aab2d8a6f7e1a85187e43220dc75e09c05e4ae29ee7f1476bc0

Observation a3b0f8e2-0f52-4b46-b802-5bb53cdb1795 · outbound

This paper cites A deep reinforcement learning approach to first-order logic theorem proving.

Partial Label Learning for Automated Theorem Proving A deep reinforcement learning approach to first-order logic theorem proving

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:18:23.627923Z digest=sha256:8fcb6f647789ba22db97958dbc46050ab957eadc63a75bc3586f519b57332cfb

Observation 96823ac8-4256-4138-9db5-41658b71e8b2 · outbound

This paper cites Partial label learning with self-guided retraining.

Partial Label Learning for Automated Theorem Proving Partial label learning with self-guided retraining

Reference 9

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doi, observed 2026-08-06T20:18:28.487494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:23.682470Z digest=sha256:16077599db44c86fbd49b8c14dc13a5abbbe77d5160817415632ae3fe0c4d09c

Observation 3b49393e-01db-4f9f-b9ca-b00e54ac9b10 · outbound

This paper cites Provably consistent partial-label learning.

Partial Label Learning for Automated Theorem Proving Provably consistent partial-label learning

Reference 10

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raw_fallback, observed 2026-08-06T20:18:29.636741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:23.797947Z digest=sha256:442848b34d65f346e41ce10d30d42574ab7c81b0b0474ac82a6d743e5f319f8e

Observation b7b320af-5664-450a-8086-c135b5d76523 · outbound

This paper cites From language to programs: Bridging reinforcement learning and maximum marginal likelihood.

Partial Label Learning for Automated Theorem Proving From language to programs: Bridging reinforcement learning and maximum marginal likelihood

Reference 11

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:23.907943Z digest=sha256:6b7e81f5e25a4704ea66a8b7baf49a98ce7a6c8a7689a3a28514dabde72952de

Observation 13362317-c7b9-4222-b81f-65e3d5633076 · outbound

This paper cites Holden and Konstantin Korovin.

Partial Label Learning for Automated Theorem Proving Holden and Konstantin Korovin

Reference 12

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doi, observed 2026-08-06T20:18:28.330663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:23.991044Z digest=sha256:2eec16984144cdc8da986a0bf9086918dba746d5f241e157fb1ab35b5fdf39f3

Observation 229f8f68-05b6-4f75-a969-95b519c156aa · outbound

This paper cites ENIGMA: efficient learning-based inference guiding machine.

Partial Label Learning for Automated Theorem Proving ENIGMA: efficient learning-based inference guiding machine

Reference 13

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doi, observed 2026-08-06T20:18:28.192680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.044152Z digest=sha256:3eaf2aa36f3ac755a20abaf46d6c5316c695019ee74e5278589d2b7cbb0b1a91

Observation 6d45a036-41f2-4f2d-8491-eebfcb12588b · outbound

This paper cites Learning with multiple labels.

Partial Label Learning for Automated Theorem Proving Learning with multiple labels

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.161207Z digest=sha256:b94486ea3c4f078eaf1e2db6362b4b97e04957aba8211935cf1989909265a42a

Observation 720d85d5-6b12-47cb-84c9-5b63c7463420 · outbound

This paper cites Mizar40 dataset, 2015.

Partial Label Learning for Automated Theorem Proving Mizar40 dataset, 2015

Reference 15

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.238113Z digest=sha256:5f3fbfab8128404389ef0ce14e1f9b45d82b14c784689ff9636f539567ddc269

Observation b8916410-795d-4c65-aec3-2c76bfeb5afa · outbound

This paper cites M2K dataset, 2018.

Partial Label Learning for Automated Theorem Proving M2K dataset, 2018

Reference 16

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raw_fallback, observed 2026-08-06T20:18:32.085485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.329605Z digest=sha256:638bf91554af9f092f2f7752f289412851ad6e15415b71b339a466724be8fe8c

Observation 2724a81c-b93e-4ca0-b5fd-8f914fb5250b · outbound

This paper cites Reinforcement learning of theorem proving.

Partial Label Learning for Automated Theorem Proving Reinforcement learning of theorem proving

Reference 17

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raw_fallback, observed 2026-08-06T20:18:31.785376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.401735Z digest=sha256:86b607437477a102b94c9980bbbcadbbdfb7aad1057373f77c75ca0dc6e806a0

Observation 0ff795fb-9bcf-4087-92f5-865b45420a89 · outbound

This paper cites Learning from multiple proofs: First experiments.

Partial Label Learning for Automated Theorem Proving Learning from multiple proofs: First experiments

Reference 18

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doi_truncated, observed 2026-08-06T20:18:27.889718Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.497386Z digest=sha256:bfe6c3669b63fbfcea46196d4e580d86dab5a3adc728f739165ac61a4e823945

Observation 6a7014ec-d336-4ded-9ec1-955f13ba9c9f · outbound

This paper cites Males: A framework for automatic tuning of automated theorem provers.

Partial Label Learning for Automated Theorem Proving Males: A framework for automatic tuning of automated theorem provers

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.618660Z digest=sha256:583413535aae87c697018300c53db6f1ed9396b60f5fc0238947ee5cde2f2379

Observation 66e305f0-9be7-46ce-a69d-56d5f64c1588 · outbound

This paper cites A conditional multinomial mixture model for superset label learning.

Partial Label Learning for Automated Theorem Proving A conditional multinomial mixture model for superset label learning

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.733212Z digest=sha256:71f78266de3b1b76dc9af238eadb30cab2ad957265168bf769a1f3ac53e6326a

Observation e883a4a6-e862-4ef0-a4ee-823ef48f9d55 · outbound

This paper cites Loos, Geoffrey Irving, Christian Szegedy, and Cezary Kaliszyk.

Partial Label Learning for Automated Theorem Proving Loos, Geoffrey Irving, Christian Szegedy, and Cezary Kaliszyk

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.895567Z digest=sha256:1b1b3f92ce0a64c108a83ce17f3865bad5a333b337bf8646442a4b5596125f20

Observation 08072c54-d773-4357-a12f-cfeef1d3ac91 · outbound

This paper cites Classification with partial labels.

Partial Label Learning for Automated Theorem Proving Classification with partial labels

Reference 22

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no resolver link, observed 2026-08-06T20:18:24.972577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:18:24.972577Z digest=sha256:c48ed93c1212e46b76351711975ee5370068ea6e76ab4dd5b028a73cd3792218

Observation 2d2fdd52-3021-475a-8882-431ec91c420e · outbound

This paper cites Property invariant embedding for automated reasoning.

Partial Label Learning for Automated Theorem Proving Property invariant embedding for automated reasoning

Reference 23

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doi, observed 2026-08-06T20:18:31.364694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.079950Z digest=sha256:830f2718508c8007d3910b8582d48a42b7337ff1fa534188b78d53d45b549a2f

Observation 2bd5c2ff-eb77-4c5e-8bd8-a76ed10882a8 · outbound

This paper cites leanCoP : lean connection-based theorem proving.

Partial Label Learning for Automated Theorem Proving leanCoP : lean connection-based theorem proving

Reference 24

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raw_fallback, observed 2026-08-06T20:18:31.031227Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.271314Z digest=sha256:8517c33955acbf76277ea8e6ceea9b59d86bf1ba533ca71fe26c2cd18a17159d

Observation 0fdf082f-29cc-41b1-b245-86666daeab2b · outbound

This paper cites Graph Representations for Higher-Order Logic and Theorem Proving.

Partial Label Learning for Automated Theorem Proving Graph Representations for Higher-Order Logic and Theorem Proving

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:18:25.433447Z digest=sha256:ac59fcd2153b4f55bd25a777f67ed9ca0a1ed39dc423ad14aae0fa9dfd65438e

Observation 29ab85c8-63ba-442b-969c-56939618e29c · outbound

This paper cites Atpboost: Learning premise selection in binary setting with atp feedback.

Partial Label Learning for Automated Theorem Proving Atpboost: Learning premise selection in binary setting with atp feedback

Reference 26

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raw_fallback, observed 2026-08-06T20:18:30.821316Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.545629Z digest=sha256:c51c0a8c7638d896edb19c871c48c018f4ccad379e51ce6f9bb803c9f7ef5afb

Observation f34112a8-0420-4e75-bd36-378f918605ae · outbound

This paper cites Breeding theorem proving heuristics with genetic algorithms.

Partial Label Learning for Automated Theorem Proving Breeding theorem proving heuristics with genetic algorithms

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.704460Z digest=sha256:ef8e6a311c6e0c990bd7a60935e8b6ad56a6e3473abdea0c83eca739ceb9257a

Observation edcbd904-06a2-410c-809f-67344d3ac2e1 · outbound

This paper cites Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm.

Partial Label Learning for Automated Theorem Proving Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

Reference 29

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no resolver link, observed 2026-08-06T20:18:25.796266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:18:25.796266Z digest=sha256:147fd9c64c6bbeb2f75ee9f390bd5ab5b7148b022c095102513db2fc6f661db6

Observation 7f8f6300-c944-4dd6-9f35-c3e145d47686 · outbound

This paper cites Partial label learning: Taxonomy, analysis and outlook.

Partial Label Learning for Automated Theorem Proving Partial label learning: Taxonomy, analysis and outlook

Reference 30

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doi, observed 2026-08-06T20:18:27.304833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.877306Z digest=sha256:320fb964a85278c76356385035dbbaa82b056a35ea5cb91b6b9d9d980b3c2a86

Observation 78a4350b-5077-4bd1-b21b-b023d1e979d8 · outbound

This paper cites Malarea: a metasystem for automated reasoning in large theories.

Partial Label Learning for Automated Theorem Proving Malarea: a metasystem for automated reasoning in large theories

Reference 31

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raw_fallback, observed 2026-08-06T20:18:30.623207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.977798Z digest=sha256:4e2ec605bc3d82307ca9c183143b05d13c8d8fcfa7734cb0b2f8e50dcc21a751

Observation 5979f221-dd68-4a7c-85c9-2726a10479c9 · outbound

This paper cites Blistr: The blind strategymaker.

Partial Label Learning for Automated Theorem Proving Blistr: The blind strategymaker

Reference 32

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doi_truncated, observed 2026-08-06T20:18:27.031705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:26.105838Z digest=sha256:d891903384d792abd101b9ac210d59c36edf068904446e05619fd1d598998cb6

Observation 5d4125c5-db6a-4c78-a3b7-b75a2130a1f0 · outbound

This paper cites Premise selection for theorem proving by deep graph embedding.

Partial Label Learning for Automated Theorem Proving Premise selection for theorem proving by deep graph embedding

Reference 33

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raw_fallback, observed 2026-08-06T20:18:30.443800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:26.250341Z digest=sha256:4a97d6b2738b6af86f6f04f1d97412f25459dfe5a9d9aaeeb3a06c9da46882c2

Observation fc523812-3f72-4a99-bbe5-b1e3e11f4f40 · outbound

This paper cites Leveraged weighted loss for partial label learning.

Partial Label Learning for Automated Theorem Proving Leveraged weighted loss for partial label learning

Reference 34

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raw_fallback, observed 2026-08-06T20:18:30.254382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:26.385965Z digest=sha256:177ae9e6d98b6dea0f4885550245a0a5744e1ac5aeb818af8b44a71be481ab9e

Observation 94cc478a-7472-4b4a-a36c-5466e57e17d5 · outbound

This paper cites an unresolved cited work.

Partial Label Learning for Automated Theorem Proving Unresolved cited work

Reference 35

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no resolver link, observed 2026-08-06T20:18:26.541100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:18:26.541100Z digest=sha256:97fdf690474b1cd35c0fd5513ca00627ac666459cf2d628a22fc36dbe0f7a798

Observation 45d45978-8f0c-403b-a9d0-e8971d606161 · outbound

This paper cites The role of entropy in guiding a connection prover.

Partial Label Learning for Automated Theorem Proving The role of entropy in guiding a connection prover

Reference 37

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no resolver link, observed 2026-08-06T20:18:26.774089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:18:26.774089Z digest=sha256:8f93ef382ff879e12a4520561249a3e04a8b9532730b00466f0b641e3e670e51

Observation c0b69a71-9c84-44e1-bcd3-31e7c9706187 · outbound

This paper cites Towards Unbiased Exploration in Partial Label Learning.

Partial Label Learning for Automated Theorem Proving Towards Unbiased Exploration in Partial Label Learning

Reference 38

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local_arxiv, observed 2026-08-06T20:18:28.626564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:18:26.884619Z digest=sha256:986e7076abbc4e1fc3240139acd442529ac94d101819f553e3ea9ca04d1d95ad

Pith citing papers

No inbound Pith citation observations are available.