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Paper Citation Record · LEDGER

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization

As of 15 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 2 inbound Pith citation observations for arXiv:2501.13959.

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

pith.paper-citation-record.v1
2501.13959 v3

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:48:52.403288Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

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

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T03:05:04.196270Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T03:09:44.071462Z

Reference resolution

31 of 31 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1d0a9d0e-ce43-49c9-ad6d-65172c6a1f34 · outbound

This paper cites write newline.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f5af39e2-6ddc-42b2-a8fc-0ac293817f6b · outbound

This paper cites The Coq proof assistant reference manual: Version 6.1.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization The Coq proof assistant reference manual: Version 6.1

Reference 2

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Source-reported events for the cited work

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

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Observation 43bffa66-5150-4e75-a67b-531dc805e3cd · outbound

This paper cites M 3-embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization M 3-embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation

Reference 3

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no resolver link, observed 2026-08-10T17:48:52.288269Z

Source-reported events for the cited work

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Observation d48db010-cd81-428f-9e32-e50e4c78d546 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization A simple framework for contrastive learning of visual representations

Reference 4

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no resolver link, observed 2026-08-10T17:48:52.292293Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-10T17:48:52.292293Z digest=sha256:2f2a7ba22e188b9772d192fd7779d302cebb292cd631f9ae769af6184faed1f5

Observation e82938ec-4363-450d-bf44-b0c1d3d81c47 · outbound

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

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization The lean theorem prover (system description)

Reference 5

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Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-10T17:48:52.296656Z digest=sha256:49ce26245654120982622c84faddc0e85766dfc313f081d4444c314176f3fd71

Observation fb0befa1-af86-4178-97ab-522f776403c2 · outbound

This paper cites BERT : Pre-training of deep bidirectional transformers for language understanding.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization BERT : Pre-training of deep bidirectional transformers for language understanding

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 64225e05-a2cc-4769-9504-e94e50f621a1 · outbound

This paper cites A semantic search engine for mathlib4.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization A semantic search engine for mathlib4

Reference 7

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no resolver link, observed 2026-08-10T17:48:52.304822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b5610de7-714d-4116-8e56-586513fc80c3 · outbound

This paper cites U ni X coder: Unified cross-modal pre-training for code representation.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization U ni X coder: Unified cross-modal pre-training for code representation

Reference 8

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no resolver link, observed 2026-08-10T17:48:52.309202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:48:52.309202Z digest=sha256:d2945aa7e31034c591935fe81d6214fa9398dc69ac232a88a2d8b1e27943a705

Observation 308f714d-67a9-4ae7-95a9-657c343399f1 · outbound

This paper cites an unresolved cited work.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Unresolved cited work

Reference 9

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Source-reported events for the cited work

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

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Observation 65156a79-f9cd-41f1-a48f-b925fc6e3d80 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Momentum contrast for unsupervised visual representation learning

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2f672643-d358-4804-85f1-b7606c21366e · outbound

This paper cites Unsupervised dense information retrieval with contrastive learning.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Unsupervised dense information retrieval with contrastive learning

Reference 11

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Unavailable: canonical work link unavailable.

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Observation d041f872-310a-46a3-91ac-99ef88c59da6 · outbound

This paper cites Dense passage retrieval for open-domain question answering.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Dense passage retrieval for open-domain question answering

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a719326f-60f7-45ab-89d8-5152facc6d1b · outbound

This paper cites Llama2vec: Unsupervised adaptation of large language models for dense retrieval.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Llama2vec: Unsupervised adaptation of large language models for dense retrieval

Reference 13

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Source-reported events for the cited work

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

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Observation b6fd052c-8720-4f08-be4a-3b54617f1f79 · outbound

This paper cites Fine-tuning llama for multi-stage text retrieval.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Fine-tuning llama for multi-stage text retrieval

Reference 14

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Unavailable: canonical work link unavailable.

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Observation 9855b852-22e0-4fed-9718-15c3bcd5009d · outbound

This paper cites P., Szegedy, C., Kuci \'n ski, ., Mi o \'s , P., and Wu, Y.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization P., Szegedy, C., Kuci \'n ski, ., Mi o \'s , P., and Wu, Y

Reference 15

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Source-reported events for the cited work

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

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Observation db9dcb6a-35e4-444e-9c4d-a78ab938c494 · outbound

This paper cites an unresolved cited work.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Unresolved cited work

Reference 16

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Source-reported events for the cited work

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

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Observation 0d9fb604-2beb-4576-aafe-e169ad204ee2 · outbound

This paper cites Passage Re-ranking with BERT.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Passage Re-ranking with BERT

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2bf71c4c-a44c-4065-bbe1-6f2826cd11e7 · outbound

This paper cites Understanding the Behaviors of BERT in Ranking.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Understanding the Behaviors of BERT in Ranking

Reference 18

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no resolver link, observed 2026-08-10T17:48:52.348333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4946cd64-e507-40b7-873d-bbc495d70e9d · outbound

This paper cites X., Dong, D., Wu, H., and Wang, H.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization X., Dong, D., Wu, H., and Wang, H

Reference 19

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no resolver link, observed 2026-08-10T17:48:52.353036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:48:52.353036Z digest=sha256:4babb8ab974c79a823fe285be6163f3dc809912670afe849ae3d7daff12d17c2

Observation a58c64f4-89b5-43a0-9662-cb9aca006b2d · outbound

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

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition

Reference 20

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Unavailable: canonical work link unavailable.

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Observation 9575f71f-8974-4dc8-bddf-80e444803586 · outbound

This paper cites The probabilistic relevance framework: Bm25 and beyond.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization The probabilistic relevance framework: Bm25 and beyond

Reference 21

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Observation c1bff264-42fc-485f-ae2f-34feda6ba232 · outbound

This paper cites and Buckley, C.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization and Buckley, C

Reference 22

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Source-reported events for the cited work

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

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Observation eea04ce8-b400-4bc6-a217-f71aebbacbc8 · outbound

This paper cites Towards large language models as copilots for theorem proving in lean.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Towards large language models as copilots for theorem proving in lean

Reference 23

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

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Observation 06e63f1a-2480-464b-81fb-d89f21e0dbaa · outbound

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Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Fast wordpiece tokenization

Reference 24

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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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-10T17:48:52.374400Z digest=sha256:4d08c61f916d245050c88a9ec3f9473a8394c53a43ad1cd902b1e265ccafabb7

Observation 23c17ea7-7b3c-487e-8c08-d30122a0f10c · outbound

This paper cites cloze procedure.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization cloze procedure

Reference 25

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Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-10T17:48:52.378349Z digest=sha256:6871f74af0637ce5aa24dc69e6bec832b85eeb9827414dbccf909d6eea0b99b5

Observation e0492c8f-a551-4271-b7fd-59386ad5ece6 · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 26

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no resolver link, observed 2026-08-10T17:48:52.382324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c0a85873-a5fe-4ec7-a760-562481fc207b · outbound

This paper cites Improving text embeddings with large language models.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Improving text embeddings with large language models

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:48:52.386582Z digest=sha256:9759f3f0fd8afbd578eafe5b5a58e3d246b256dd0dbd259ddf1f54aafe919de0

Observation 114ee808-94e9-4966-926f-f7902dd196ce · outbound

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Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization and Saha, R

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-10T17:48:52.591734Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-10T17:48:52.390447Z digest=sha256:bbce0bb19c5e1181e5cf2ca35f372dd0fae890c851a38882c01ea15dcf5589b5

Observation dced5e3e-9e53-4f2c-9cff-a47342f69036 · outbound

This paper cites Byt5: Towards a token-free future with pre-trained byte-to-byte models.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization Byt5: Towards a token-free future with pre-trained byte-to-byte models

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-10T17:48:52.577894Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-10T17:48:52.395587Z digest=sha256:1cdd37b2d29cd7aaebd314640a7df83ca5942a4112cbaccab51e2282b2f99fca

Observation b11c937c-4d2c-49e4-bd9a-58d2eef3e9d1 · outbound

This paper cites J., and Anandkumar, A.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization J., and Anandkumar, A

Reference 30

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Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-10T17:48:52.399254Z digest=sha256:84b5b806f1aeb60da647012b3713565d90de323869c059c43f6976e29e78c3a0

Observation e9132bc6-9fdf-4ec1-9d56-ad12d468f0e5 · outbound

This paper cites M., and Polu, S.

Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization M., and Polu, S

Reference 31

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Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-10T17:48:52.403288Z digest=sha256:0780df4e5f67a027a61508abe481081dd4e0c43325ccc5bc7e6fd282fbb54e74

Pith citing papers

Observation 21bbab78-48ea-4dd5-89dd-402d2e252c0f · inbound

LeanSearch v2: Global Premise Retrieval for Lean 4 Theorem Proving cites this paper.

LeanSearch v2: Global Premise Retrieval for Lean 4 Theorem Proving Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization

Reference 20

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arxiv_id, observed 2026-05-14T18:32:34.207696Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-14T18:32:24.957899Z digest=sha256:9b0f2b71c70ac16719bebd58767cd8558c62f94c737f9feb74466dd0bb321c75

Observation 5ae5b4f7-d02c-4e3d-bafd-99021e55c86d · inbound

LeanSearch v2: Global Premise Retrieval for Lean 4 Theorem Proving cites this paper.

LeanSearch v2: Global Premise Retrieval for Lean 4 Theorem Proving Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization

Reference 20

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arxiv_id, observed 2026-05-15T03:09:44.077495Z

Source-reported events for the cited work

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

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