Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-12T03:38:39.738401Z
Paper Citation Record · LEDGER
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data
As of 17 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 1 inbound Pith citation observation for arXiv:2605.10129.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T05:33:53.927154Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T05:33:56.202284Z
Reference resolution
62 of 62 outbound references displayed
- verified exact3
- verified fuzzy50
- unresolved1
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- malformed identifier0
- metadata mismatch8
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation d287a732-f633-40f0-bdb6-6b9b80251e28 · outbound
This paper cites 2025 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2025 , eprint =
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.235488Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0f259c7e-1e20-426c-a65a-596c85b38de7 · outbound
This paper cites 2020 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2020 , eprint =
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.199058Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f9adb72c-2e3d-4924-a6b8-36338f9189dc · outbound
This paper cites 2023 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2023 , eprint =
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.250841Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d70c2b7c-5b01-4234-989b-5dc30519babd · outbound
This paper cites 2023 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2023 , eprint=
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.269897Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ed854f06-72b2-4435-8c32-7352400f8dff · outbound
This paper cites 2016 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2016 , eprint=
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.218638Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 492389c6-3cdf-4966-b087-780a0dd86bdb · outbound
This paper cites 2023 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2023 , eprint=
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.207303Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cda71a16-1d14-48d0-abb4-c7ab090cec4e · outbound
This paper cites Journal of machine learning research , volume=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Journal of machine learning research , volume=
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.180878Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e1e2027e-3cc9-4d7c-b501-64368c06d202 · outbound
This paper cites 2024 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2024 , eprint=
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.191776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 23329a6c-f76c-4ccf-8c70-bc261f15e40e · outbound
This paper cites 2024 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2024 , eprint=
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.170042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b083a3ea-d17a-4322-b4a4-218451aee362 · outbound
This paper cites 2019 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2019 , eprint=
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.354528Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 42705cf6-c977-4fa7-90a3-f7a193ee31eb · outbound
This paper cites Proceedings of the 26th annual international conference on machine learning , pages=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Proceedings of the 26th annual international conference on machine learning , pages=
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.223503Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8801d9af-1640-48ab-9a77-54508cb3cb07 · outbound
This paper cites 2023 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2023 , eprint=
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.227068Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 17be6ef5-e260-4893-9a65-ecb99ea4d1a9 · outbound
This paper cites 2024 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2024 , eprint=
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.195417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8eced79e-cccc-4ff8-b469-05e0efe860c1 · outbound
This paper cites 2024 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2024 , eprint=
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.211449Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2cf2127d-59fe-421d-ba7a-84a4d3443ced · outbound
This paper cites an unresolved cited work.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Unresolved cited work
Reference 15
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T18:46:46.166265Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 818872a7-d3eb-4101-802f-0326c69cc1df · outbound
This paper cites 2022 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2022 , eprint=
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.184085Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 77783ced-bd0d-459a-95fc-263252d0dd7c · outbound
This paper cites 2023 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2023 , eprint=
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.297101Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation aa669298-61bf-4744-8685-1e8843bf5820 · outbound
This paper cites 2019 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2019 , eprint=
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.285995Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 729c4318-0ba5-45a6-9d26-c0fa65bbcf1b · outbound
This paper cites 2019 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2019 , eprint=
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.262744Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ea8cd691-c147-4be3-9c6e-1cd2a79187c3 · outbound
This paper cites 2021 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2021 , eprint=
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.215510Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 151dd78a-33bb-4d9c-8229-fa6b5c263b65 · outbound
This paper cites 2022 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2022 , eprint=
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.187708Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 83e16d8b-c117-4cbc-b555-b4dab99d6b0e · outbound
This paper cites 2019 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2019 , eprint=
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.331131Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0a8fc2e3-8365-454a-a081-3f61172562cd · outbound
This paper cites 2020 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2020 , eprint =
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.174153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation bab011ff-3097-4ebf-875a-92c60c30327a · outbound
This paper cites 2019 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2019 , eprint =
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.277811Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7a7996d2-c3f0-46d2-9a89-3c701e2a78ce · outbound
This paper cites 2026 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2026 , eprint =
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.281584Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation eee5a271-277a-45df-96d3-25c7bc40e090 · outbound
This paper cites 2023 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2023 , eprint =
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.202583Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c7faa5e0-1d93-4e99-934e-81db9b9eb64e · outbound
This paper cites 2023 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2023 , eprint=
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.266309Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8adb8273-210c-4925-a467-a2cfa94f928c · outbound
This paper cites 2026 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2026 , eprint=
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.254198Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a8a15e44-01f1-4ff9-b07c-deb67889f734 · outbound
This paper cites 2025 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2025 , eprint =
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.300681Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e830adf2-4980-4f5d-85c2-ec17dd9d9d43 · outbound
This paper cites 2025 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2025 , eprint =
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.289798Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 3b04163b-91ee-4411-baa7-d9cb8037a424 · outbound
This paper cites 2026 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2026 , eprint =
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.293490Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a89f1628-0e46-41c9-839c-bd4fd3848a24 · outbound
This paper cites 2025 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2025 , eprint =
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.361687Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2cadef74-2d1d-473a-ac86-086e18866327 · outbound
This paper cites 2025 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2025 , eprint=
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.346507Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 386ee380-9276-4481-a806-2fe871be326d · outbound
This paper cites 2021 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2021 , eprint=
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.239097Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 98f4ac27-a15c-43ca-b9bf-329a73edf8b8 · outbound
This paper cites 2023 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2023 , eprint=
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.315702Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a1dde3cc-463c-4e10-b40e-47f365573326 · outbound
This paper cites CharBERT: Character-aware Pre-trained Language Model , url=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data CharBERT: Character-aware Pre-trained Language Model , url=
Reference 36
- Resolution
- verified exact
- doi, observed 2026-05-12T03:41:18.830806Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f474ad41-ac19-4da7-b030-f79182ae960c · outbound
This paper cites 2021 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2021 , eprint=
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.308062Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c9e6492b-11b5-407d-8de9-2d6863e5f9ec · outbound
This paper cites 2026 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2026 , eprint=
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.350569Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ed5f108a-2c36-483c-b909-90f0b6ec5655 · outbound
This paper cites Proceedings of the fifth annual workshop on Computational learning theory , pages=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Proceedings of the fifth annual workshop on Computational learning theory , pages=
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.327322Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c4e001ab-636e-48ba-b855-595511b6f612 · outbound
This paper cites echo state.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data echo state
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.358329Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation bc94a105-5148-4b79-934d-b73e858c5e5e · outbound
This paper cites Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics , pages=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics , pages=
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.304091Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 99ebdd60-b139-45b0-b786-47c73094e184 · outbound
This paper cites DataComp-LM: In search of the next generation of training sets for language models.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data DataComp-LM: In search of the next generation of training sets for language models
Reference 42
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T22:58:17.761776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 12747c7f-6f4d-43f5-9509-588a0e47b182 · outbound
This paper cites Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
Reference 43
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T07:11:25.676262Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 978ced0b-b564-494d-bc32-4d9e41158f5d · outbound
This paper cites Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset
Reference 44
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T07:11:25.667213Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 415dda88-a562-4c8b-923e-7f92fc27e751 · outbound
This paper cites 2021 , eprint=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2021 , eprint=
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.342644Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation bbac2115-6314-4e2b-9496-5cf873fe255e · outbound
This paper cites 2018 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2018 , eprint =
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.243722Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7aef18a7-ab57-4e18-89dc-bdae0e7560fe · outbound
This paper cites 2018 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2018 , eprint =
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.322396Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e1fc255c-527b-42af-a14e-540b78c0ce87 · outbound
This paper cites 2023 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2023 , eprint =
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.257814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f8716b3e-fecc-4f62-8bef-5d1f815cf7fb · outbound
This paper cites 2024 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2024 , eprint =
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.319101Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f7c53a5a-a6e7-4cac-91bc-17cc28b58910 · outbound
This paper cites What's In My Big Data?.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data What's In My Big Data?
Reference 50
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T07:11:25.726433Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0d35ce35-d6a4-488b-9bc9-9718ee2571b9 · outbound
This paper cites Physics of Language Models: Part 3.1, Knowledge Storage and Extraction.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Physics of Language Models: Part 3.1, Knowledge Storage and Extraction
Reference 51
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- arxiv_id, observed 2026-05-12T07:11:25.715025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ab0cf40e-d3e9-400d-8816-7ab6d0e3cd69 · outbound
This paper cites Physics of Language Models: Part 3.3, Knowledge Capacity Scaling Laws.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Physics of Language Models: Part 3.3, Knowledge Capacity Scaling Laws
Reference 52
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T07:11:25.645042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f8e2c283-87ae-4273-9e98-9c468ff3cbf6 · outbound
This paper cites IEEE transactions on neural networks and learning systems , volume =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data IEEE transactions on neural networks and learning systems , volume =
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.247430Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d321721b-aada-470a-9cee-26bc89547039 · outbound
This paper cites A Survey on Data Selection for Language Models.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data A Survey on Data Selection for Language Models
Reference 54
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T07:11:25.683736Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 06f56ca4-35e0-4986-a6f7-3aed6d7455d1 · outbound
This paper cites FastText.zip: Compressing text classification models.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data FastText.zip: Compressing text classification models
Reference 55
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T07:11:25.705591Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 496b429d-ddda-4fc9-8345-f0245b0a4046 · outbound
This paper cites 2019 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2019 , eprint =
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.334728Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2dbfe5d2-7f6c-4204-8f81-f212719b6796 · outbound
This paper cites Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:11:25.660670Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation bd638b21-2036-4d50-a4a9-d7d365f2c294 · outbound
This paper cites 2017 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2017 , eprint =
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.338810Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7a065798-f2c1-4324-aacd-0ad011cb591a · outbound
This paper cites 2017 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2017 , eprint =
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.311794Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 39960009-aeb8-413c-8ac2-00a2f6c3188d · outbound
This paper cites 2023 , eprint =.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data 2023 , eprint =
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.231678Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c22bcc74-a081-485b-b914-a2ce1f2d7e9e · outbound
This paper cites Findings of the Association for Computational Linguistics: EMNLP 2024 , pages=.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Findings of the Association for Computational Linguistics: EMNLP 2024 , pages=
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T18:46:46.274025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 62030f58-7b87-407a-b593-e6793d47850c · outbound
This paper cites Transformers Pretrained on Procedural Data Contain Modular Structures for Algorithmic Reasoning.
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Transformers Pretrained on Procedural Data Contain Modular Structures for Algorithmic Reasoning
Reference 62
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- verified exact
- arxiv_id, observed 2026-05-12T07:11:25.693145Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
Observation 5ca3996f-5305-417f-86a2-e3e2e34cfb33 · inbound
Logic Before Language: Pre-pretraining on Formal Derivations Fosters Skill Acquisition and Compressibility cites this paper.
Logic Before Language: Pre-pretraining on Formal Derivations Fosters Skill Acquisition and Compressibility Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T05:33:56.215173Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.