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Paper Citation Record · LEDGER

Partial Label Learning for Automated Theorem Proving

As of 21 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 2026-08-21T06:32:19.484+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=sha256:6f8ed538262730243763b1ecf828229fd277d206fb962c573982b2dee9e665fe

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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raw_fallback, observed 2026-08-06T20:18:30.041030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:22.798590Z digest=sha256:a5b7ad1b02ef1b9db45f116ecbdb6e063121d41a69acda5fb6ee299f6190903b

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:22.901507Z digest=sha256:2399fcd118205eabf7d70830e72af6aa34556e4d77fd3d8b44ce56bb62a605e9

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

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source=arxiv_source observed=2026-08-06T20:18:23.091803Z digest=sha256:73df6d02a55a9cc63da1135aad838bee2f7cec8ed0eab7a5270dff448ed74b0d

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:23.221471Z digest=sha256:5528910eea7b4afda463196ef30266de103ba4247379cfac459881670b2176a2

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=sha256:6b044a7f8bb93f2d43a1a1ef6862e1d6a961bc407f4a71022832d29404e694fc

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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raw_fallback, observed 2026-08-06T20:18:32.681808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:23.517382Z digest=sha256:8c235a56068cc4d6fb608f61e288b30dcfb2143ed0cf8323624df5eb7b4e02e1

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:acfb5a1c3b6dd4475177684a3717533095fca97e3fafcf2d274da4884372d653

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:23.682470Z digest=sha256:24087ef1129dbd4615de6914139075760467815ccf6dbad9a1b3edfb98576cef

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:23.797947Z digest=sha256:7eb2c0fead65662ef9d8f66cdebfb5b4dbab8bff408b8006fb0738ae779fcc8a

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:23.907943Z digest=sha256:d562b826b283d0c7705bcb3e93f33aaaf4760e21ee00fff21b0f116e04cf6ceb

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 2026-08-21T06:32:19.484+00:00.

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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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.044152Z digest=sha256:d568d78f18f08416ada47a3f4ecd075619d73c50d8190f01ee7b24fc2cdbe468

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.161207Z digest=sha256:67025235b272f47cad585d53d64cc275a510950ed775468ca2dd881824ebcf02

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.238113Z digest=sha256:c0bf196cc2933010653cee58324de996d09507246e834346f10821620ba290a5

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.329605Z digest=sha256:894e259a9b462edbc4aaaaae6c057509be2da1150ae79ad194315f2a67a4cb1f

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.401735Z digest=sha256:857d9d5cee4186f8cdf9960c9e9b4a161a64b4fdaedbd4420ae6a6ea70fcafbb

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.497386Z digest=sha256:9c72514187393a2e3524a69aebfaa22c8ac5967e993e4af5eaf0da280981ff45

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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doi, observed 2026-08-06T20:18:27.666856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.618660Z digest=sha256:65b1be4f75631a2c1259db97a470fd531662b5db3f05e444d882a45b7bc7f61e

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.733212Z digest=sha256:33175df7bad855700f18e96544ca26c49b39a1e284574f1dde3247067ec48181

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:24.895567Z digest=sha256:ad866a493bd7667459dda6e31a4f91caa7fa8895d19473d68a81f5a9dfefca7e

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:abe0621f4fbf5e0dab47a3672d4d945f09d835681773bed1d6c70c0de5571255

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

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.079950Z digest=sha256:2065f39bd49dade9ca131aca9c5d004e27758237e37c9f8f43ea01d66e357ca3

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.271314Z digest=sha256:97b61124399c7e6e16bcf98752cf847a5ab35fc8dfa41fbcdca0279555a66161

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:c46641f0492d906e368061d15dbbb75ef1fe709fd674d765f4d34389eb0c6c73

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.545629Z digest=sha256:27154d3ba95627c459d39902ef1d0bbc114fdbf82228028ffffe109f767b1d4a

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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doi_truncated, observed 2026-08-06T20:18:27.443338Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.704460Z digest=sha256:bd3324a2b89087e28c873cbffc13a17a2793c00d013485f42c34cc488f267d80

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=sha256:7d261dcb2c4ee677b4b07f4efe0b6dde2c5730659d827741f80ab1a139bcd44a

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.877306Z digest=sha256:7a80f43c28391698d882f80f16adba0965f7c0bf8fa06e44d3745e871c38795b

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:25.977798Z digest=sha256:53ad4b724a327b7cf4cfb7e9af8487504dc87ff920e88e1534dcc0c89669bd7b

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:26.105838Z digest=sha256:843770c349820cb9f882a1fdf5ebc7770af79973d0a42d25b1369b80eae156d5

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:26.250341Z digest=sha256:e846b70952cebd844e27a255ab21e7fab84222c3a8e46cc4ca9b79cb93955daa

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:26.385965Z digest=sha256:5204c7f1caff4ed28fea82d3f46c1c4d051d9a9f2cce92a8c128527d6e09bdbb

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=sha256:43fe2494a4e426be4fa73f43286638d07fef101fb0ab883bc4c095f399c50328

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=sha256:6dc4618aa635fd7918f08e8608371625651405bdf270ac297188893e119dfe4d

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-06T20:18:26.884619Z digest=sha256:355d9eed8c0f7a976ff11a809a4041eb22217a73c8d53ec181acb2ed236fdcec

Pith citing papers

No inbound Pith citation observations are available.