Paper Citation Record · LEDGER

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving

As of 22 July 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2604.23712.

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

pith.paper-citation-record.v1
2604.23712 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-08T06:33:29.860024Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-21T06:31:05.380196+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

35 of 35 outbound references displayed

verified exact9
verified fuzzy22
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7e3a12e5-a8f9-42fa-876c-a72a0125441f · outbound

This paper cites Large Language Models for Mathematical Reasoning: Progresses and Challenges.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:11:16.038853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 9f9bb27f-15b2-4784-8dd3-4b55fb6d537f · outbound

This paper cites G., Rowland, M., Piot, B., Guo, D., Calandriello, D., Valko, M., and Munos, R.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving G., Rowland, M., Piot, B., Guo, D., Calandriello, D., Valko, M., and Munos, R

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.860575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation c12557f2-9b13-4471-8e67-1314685742a0 · outbound

This paper cites Language Model-Driven Data Pruning Enables Efficient Active Learning.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Language Model-Driven Data Pruning Enables Efficient Active Learning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:11:16.056019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 3ca993fc-af3e-4fcd-8a0f-af71d593cd75 · outbound

This paper cites ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T21:11:16.429344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 28124d47-16d9-468e-8d90-36914e3062c5 · outbound

This paper cites AlpaGasus: Training A Better Alpaca with Fewer Data.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving AlpaGasus: Training A Better Alpaca with Fewer Data

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:11:16.224860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation c56d36bd-8dca-48c1-981f-fe8c2bd8600f · outbound

This paper cites F., Leike, J., Brown, T., Martic, M., Legg, S., and Amodei, D.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving F., Leike, J., Brown, T., Martic, M., Legg, S., and Amodei, D

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.864748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 7df10993-f633-407a-9b35-5b16e011f462 · outbound

This paper cites The Lean theorem prover (system description).

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving The Lean theorem prover (system description)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.886995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 6083e5aa-3b4d-48e0-bde7-594bf63c920e · outbound

This paper cites Olympiadbench: A challenging benchmark for promoting AGI with Olympiad-level bilingual multimodal scientific problems.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Olympiadbench: A challenging benchmark for promoting AGI with Olympiad-level bilingual multimodal scientific problems

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.929473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 1c13236a-518c-41ba-bf60-96af5064a90c · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Measuring Mathematical Problem Solving With the MATH Dataset

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.878639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation c71172af-f49d-49e8-a989-2f162de86f50 · outbound

This paper cites A., Milan, K., Quan, J., Ramalho, T., Grabska-Barwinska, A., et al.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving A., Milan, K., Quan, J., Ramalho, T., Grabska-Barwinska, A., et al

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.873278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 6747dfb0-889e-4dca-9cf5-793139262ee5 · outbound

This paper cites Hypertree proof search for neural theorem proving.Advances in neural information processing systems, 35: 26337–26349.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Hypertree proof search for neural theorem proving.Advances in neural information processing systems, 35: 26337–26349

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.869302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation f120df8d-f7f8-4cd0-8892-dd5de4338cd8 · outbound

This paper cites Solving Quantitative Reasoning Problems with Language Models.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Solving Quantitative Reasoning Problems with Language Models

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.946833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation b51095ee-e38f-443c-9e12-3df71fa5a014 · outbound

This paper cites Formalization of Convergence Rates of Four First-order Algorithms for Convex Optimization.Journal of Automated Reasoning, 69(4):28.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Formalization of Convergence Rates of Four First-order Algorithms for Convex Optimization.Journal of Automated Reasoning, 69(4):28

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.951477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation d92759c9-6b65-4d7d-95f5-3c84041b5420 · outbound

This paper cites Formalization of algorithms for optimization with block structures.Science China Mathematics, pp.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Formalization of algorithms for optimization with block structures.Science China Mathematics, pp

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.925285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 75a4ae66-6e11-4504-817b-32f56bd9b226 · outbound

This paper cites Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:53:10.886894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation f11c1a61-e4de-433f-8991-a98c7ac23418 · outbound

This paper cites Not all tokens are what you need for pretraining.Advances in Neural Information Processing Systems, 37:29029–29063.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Not all tokens are what you need for pretraining.Advances in Neural Information Processing Systems, 37:29029–29063

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.920027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 59980aa6-5f11-44a2-9d88-46b74d9f5c4b · outbound

This paper cites SimPO: Simple Preference Optimization with a Reference-Free Reward.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving SimPO: Simple Preference Optimization with a Reference-Free Reward

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.937714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 6fb9e6b9-4bb9-4140-a82a-6588d2959b98 · outbound

This paper cites an unresolved cited work.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Unresolved cited work

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.942866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 63ca1b53-88f2-47d2-a7e4-cd86d00b4029 · outbound

This paper cites an unresolved cited work.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Unresolved cited work

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.916137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 4f356697-8bbd-46bc-bfd3-fd03b8ff020b · outbound

This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.903106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 97a239b6-4d73-4118-bb97-4bd9e8e2cd3c · outbound

This paper cites Generative Language Modeling for Automated Theorem Proving.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Generative Language Modeling for Automated Theorem Proving

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-23T05:18:10.906922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation d2d1ddaf-87ec-461b-94dc-5549628134ac · outbound

This paper cites D., Ermon, S., and Finn, C.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving D., Ermon, S., and Finn, C

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.882599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 21f975f1-c9ee-4d91-8915-d2ccfec90f15 · outbound

This paper cites DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-15T09:32:05.843709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 65825c25-f0e1-4d10-85bf-e91828827acb · outbound

This paper cites Princeton Landmarks in Mathematics and Physics.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Princeton Landmarks in Mathematics and Physics

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.912467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 5fe87a81-c9c6-422d-a993-2137ebfefc9f · outbound

This paper cites REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.898853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 2a337b71-a865-4369-94b3-4538e7af2c2c · outbound

This paper cites Springer.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Springer

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.907666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 24d45de2-b825-4ed7-97c7-583722be66e1 · outbound

This paper cites Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T18:32:40.989755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 07bcc84e-d230-4221-a353-5d73449877cc · outbound

This paper cites Mitigating forgetting in llm fine-tuning via low-perplexity token learning.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Mitigating forgetting in llm fine-tuning via low-perplexity token learning

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T21:11:16.188406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 1e6e8112-17a8-4f4e-aeb2-a42ef4645b8d · outbound

This paper cites Internlm2.5-stepprover: Advancing automated theorem proving via expert iteration on large-scale lean problems.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Internlm2.5-stepprover: Advancing automated theorem proving via expert iteration on large-scale lean problems

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:11:16.359560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation d58fc311-bb39-4172-b416-8efe706bf624 · outbound

This paper cites M., Santurkar, S., Ma, T., and Liang, P.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving M., Santurkar, S., Ma, T., and Liang, P

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.933245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation af3dfae8-3033-450e-9d6e-78f6d1165f70 · outbound

This paper cites Bfs-prover: Scalable best-first tree search for LLM-based automatic theorem proving.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Bfs-prover: Scalable best-first tree search for LLM-based automatic theorem proving

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.894893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation a6e91168-0f5d-4627-a28d-6a26ef2a4dc6 · outbound

This paper cites CoRR , volume =.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving CoRR , volume =

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T21:11:16.441028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 9f16a0ea-aac0-4302-9aaf-4e2841615548 · outbound

This paper cites J., and Anandkumar, A.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving J., and Anandkumar, A

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T18:42:51.890869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation fb3ea233-d89d-488a-8b38-3707d39e6771 · outbound

This paper cites DeepTheorem: Advancing LLM Reasoning for Theorem Proving Through Natural Language and Reinforcement Learning.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving DeepTheorem: Advancing LLM Reasoning for Theorem Proving Through Natural Language and Reinforcement Learning

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:11:16.211148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 0ee2d959-77aa-4f9c-b8ea-f9e33e5583d9 · outbound

This paper cites MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-16T20:03:04.481585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Pith citing papers

No inbound Pith citation observations are available.