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Paper Citation Record · LEDGER

Understanding Reasoning from Pretraining to Post-Training

As of 7 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2607.16097.

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

pith.paper-citation-record.v1
2607.16097 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T21:26:36.017309Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

51 of 51 outbound references displayed

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External citation measurements

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Outbound references

Observation 78c1ecb4-d656-4c8d-ba3f-de8d4f0e6350 · outbound

This paper cites Human-aligned Chess with a Bit of Search.

Understanding Reasoning from Pretraining to Post-Training Human-aligned Chess with a Bit of Search

Reference 1

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source=arxiv_source observed=2026-08-01T21:26:32.196479Z digest=sha256:07ed556f924db076b80e0caa20fa852c7ee2f30e2e74574197d301a875bdf10e

Observation 24b31eb4-1cc8-4f77-b48a-95641d23a195 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Understanding Reasoning from Pretraining to Post-Training Advances in Neural Information Processing Systems , volume=

Reference 2

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source=arxiv_source observed=2026-08-01T21:26:32.245778Z digest=sha256:960d59a043e3a9854d1a96d6d600a70bd3f1796b874b3c7dcd2065b4676c2cd0

Observation b0bc2b55-2ce2-4f5c-936b-f1642c36a28b · outbound

This paper cites Qwen3 Technical Report.

Understanding Reasoning from Pretraining to Post-Training Qwen3 Technical Report

Reference 3

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Observation 4ca9d9e2-8735-488a-ab05-c3bda2e0d27b · outbound

This paper cites HybridFlow: A Flexible and Efficient RLHF Framework.

Understanding Reasoning from Pretraining to Post-Training HybridFlow: A Flexible and Efficient RLHF Framework

Reference 4

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Observation cebc0c53-dddb-4c49-8821-ec843289af4d · outbound

This paper cites Scaling Laws for Neural Language Models.

Understanding Reasoning from Pretraining to Post-Training Scaling Laws for Neural Language Models

Reference 5

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source=arxiv_source observed=2026-08-01T21:26:32.456353Z digest=sha256:a38a3fe47ff61b7bf70479b2bf640922cff21422ab0ff22f9e9bc1970dcbaaa6

Observation c354859d-0e8c-448e-8406-5892327cbe32 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Understanding Reasoning from Pretraining to Post-Training Training Compute-Optimal Large Language Models

Reference 6

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source=arxiv_source observed=2026-08-01T21:26:32.517791Z digest=sha256:e46b9dba2939366d27e09240e932c1719f4b8578f1a00ad76e35d59624b3c40d

Observation 45fc3c09-1649-4265-b169-8500af46fc1a · outbound

This paper cites arXiv preprint arXiv:2509.21016 , year=.

Understanding Reasoning from Pretraining to Post-Training arXiv preprint arXiv:2509.21016 , year=

Reference 7

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source=arxiv_source observed=2026-08-01T21:26:32.556078Z digest=sha256:871ce1ae0f7a5e66380509a61153e1da451118c34a4a539474c5c66d595aed13

Observation 626e3a08-4e60-4c35-907e-4d49baadecca · outbound

This paper cites Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process.

Understanding Reasoning from Pretraining to Post-Training Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process

Reference 8

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Observation b6ae222a-ec23-46e0-b510-42e7fb47b6a1 · outbound

This paper cites arXiv preprint arXiv:2509.25123 , year=.

Understanding Reasoning from Pretraining to Post-Training arXiv preprint arXiv:2509.25123 , year=

Reference 9

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Observation b84ad023-1d0f-4acb-8a1b-f1c422cb1437 · outbound

This paper cites The Art of Scaling Reinforcement Learning Compute for LLMs.

Understanding Reasoning from Pretraining to Post-Training The Art of Scaling Reinforcement Learning Compute for LLMs

Reference 10

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source=arxiv_source observed=2026-08-01T21:26:32.726200Z digest=sha256:cc32310d19966e6f0bba3f43547d50f14812bed9dad72735681431d94bf490af

Observation c70e37f8-63be-4dba-b5d7-78eeefc9767f · outbound

This paper cites arXiv preprint arXiv:2512.07783 , year=.

Understanding Reasoning from Pretraining to Post-Training arXiv preprint arXiv:2512.07783 , year=

Reference 11

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Observation 92239618-bc87-45f7-950c-e08f769ec455 · outbound

This paper cites arXiv preprint arXiv:2506.16029 , year=.

Understanding Reasoning from Pretraining to Post-Training arXiv preprint arXiv:2506.16029 , year=

Reference 12

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Observation 1a3a5358-4373-4775-9e9e-8879069c263a · outbound

This paper cites Forty-first International Conference on Machine Learning , year=.

Understanding Reasoning from Pretraining to Post-Training Forty-first International Conference on Machine Learning , year=

Reference 13

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Observation 5b0e64e7-b806-40ff-a5b4-d7e81e974fcf · outbound

This paper cites When Can LLMs Learn to Reason with Weak Supervision?.

Understanding Reasoning from Pretraining to Post-Training When Can LLMs Learn to Reason with Weak Supervision?

Reference 14

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source=arxiv_source observed=2026-08-01T21:26:33.106406Z digest=sha256:ac1b04935d239c35bfd5c6d5f546f199417723694abbed1a05c4fa6ebeb1592e

Observation a45fb5e0-7c75-4a33-82a4-4f8f70bba4ed · outbound

This paper cites Nature , volume=.

Understanding Reasoning from Pretraining to Post-Training Nature , volume=

Reference 15

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Observation 9b6e379a-522a-4a4b-8ec7-34e3ae3ab709 · outbound

This paper cites Large Language Model Guided Tree-of-Thought.

Understanding Reasoning from Pretraining to Post-Training Large Language Model Guided Tree-of-Thought

Reference 16

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source=arxiv_source observed=2026-08-01T21:26:33.265609Z digest=sha256:1ca7317b4e959393f50460e9e7f001393448de77d440d5a7a3324c26ae573e99

Observation 08f6bcbd-825e-4aa6-a44a-bc9b8da73d75 · outbound

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

Understanding Reasoning from Pretraining to Post-Training Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

Reference 17

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Observation 4a5557aa-a76f-4593-86ce-5065c85fd2cc · outbound

This paper cites Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?.

Understanding Reasoning from Pretraining to Post-Training Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

Reference 18

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Observation 4799bc1c-e8c3-4fe1-95fe-fecb6d52b39d · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Understanding Reasoning from Pretraining to Post-Training Advances in Neural Information Processing Systems , volume=

Reference 19

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Observation 409cf8b7-2a5f-430f-8756-d6a2e22989b6 · outbound

This paper cites arXiv preprint arXiv:2510.15020 , year=.

Understanding Reasoning from Pretraining to Post-Training arXiv preprint arXiv:2510.15020 , year=

Reference 20

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Observation 8806f68c-2a92-4957-9c86-840f6788134a · outbound

This paper cites Reasoning with Sampling: Your Base Model is Smarter Than You Think.

Understanding Reasoning from Pretraining to Post-Training Reasoning with Sampling: Your Base Model is Smarter Than You Think

Reference 21

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Observation 8a1576f0-0758-4d8b-93da-12f169afbe46 · outbound

This paper cites arXiv preprint arXiv:2603.24844 , year=.

Understanding Reasoning from Pretraining to Post-Training arXiv preprint arXiv:2603.24844 , year=

Reference 22

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Observation 3108f45c-5ee9-4bf9-99c1-a35a01ca66e3 · outbound

This paper cites International Conference on Learning Representations , volume=.

Understanding Reasoning from Pretraining to Post-Training International Conference on Learning Representations , volume=

Reference 23

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Observation b0ff0808-fe3f-49b6-8fff-7ecd19d83944 · outbound

This paper cites arXiv preprint arXiv:2510.03264 , year=.

Understanding Reasoning from Pretraining to Post-Training arXiv preprint arXiv:2510.03264 , year=

Reference 24

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Observation 9a5d67da-066c-4e9a-9def-35c2a8f57ba4 · outbound

This paper cites RL Excursions during Pre-Training: Re-examining Policy Optimization for LLM training.

Understanding Reasoning from Pretraining to Post-Training RL Excursions during Pre-Training: Re-examining Policy Optimization for LLM training

Reference 25

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Observation ea635115-ac45-4d79-8c01-04e2eec82f04 · outbound

This paper cites Overtrained Language Models Are Harder to Fine-Tune.

Understanding Reasoning from Pretraining to Post-Training Overtrained Language Models Are Harder to Fine-Tune

Reference 26

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Observation 23efc518-9d68-4987-9e7c-d30238763bf6 · outbound

This paper cites DeepSeek-V3 Technical Report.

Understanding Reasoning from Pretraining to Post-Training DeepSeek-V3 Technical Report

Reference 27

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Observation 784ade2e-5bac-4cbe-abaf-ac0d8f2f6811 · outbound

This paper cites 2003 , publisher=.

Understanding Reasoning from Pretraining to Post-Training 2003 , publisher=

Reference 28

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Observation fdab7b28-675e-48c1-853b-0c0ea6516391 · outbound

This paper cites an unresolved cited work.

Understanding Reasoning from Pretraining to Post-Training Unresolved cited work

Reference 29

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Observation 6d29db7a-b219-4134-ae32-310a7918d01d · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Understanding Reasoning from Pretraining to Post-Training Training Verifiers to Solve Math Word Problems

Reference 30

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Observation 77660dd6-614d-41b8-b6d4-c78b36dbc429 · outbound

This paper cites Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment.

Understanding Reasoning from Pretraining to Post-Training Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment

Reference 31

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Observation 8bd31739-576a-4b1c-85d7-c12eb9916ab5 · outbound

This paper cites Olmo 3.

Understanding Reasoning from Pretraining to Post-Training Olmo 3

Reference 32

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Observation e725fcb1-eca8-4e91-8e3f-0c858c3bdd0b · outbound

This paper cites Notion Blog , volume=.

Understanding Reasoning from Pretraining to Post-Training Notion Blog , volume=

Reference 33

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Observation cd460ae0-bd66-41f7-a510-52a33a7802e0 · outbound

This paper cites 2 OLMo 2 Furious.

Understanding Reasoning from Pretraining to Post-Training 2 OLMo 2 Furious

Reference 34

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Observation 937a5172-5451-4180-b85c-fd5f55e941b1 · outbound

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Understanding Reasoning from Pretraining to Post-Training Hugging Face repository , howpublished =

Reference 35

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Observation b6844668-ff3a-4f18-bbd6-daf0aabebbad · outbound

This paper cites arXiv preprint arXiv:2512.15489 , year=.

Understanding Reasoning from Pretraining to Post-Training arXiv preprint arXiv:2512.15489 , year=

Reference 36

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Observation 28e949f9-a828-4357-bdb5-b64bf1caffa6 · outbound

This paper cites International Conference on Learning Representations , volume=.

Understanding Reasoning from Pretraining to Post-Training International Conference on Learning Representations , volume=

Reference 37

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Observation 53615201-a48e-4812-9c48-2a8b6d14d0b2 · outbound

This paper cites Proceedings of the 41st International Conference on Machine Learning , articleno =.

Understanding Reasoning from Pretraining to Post-Training Proceedings of the 41st International Conference on Machine Learning , articleno =

Reference 38

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Observation 709bf90f-e0d2-48f8-b25b-5349a2feb3bb · outbound

This paper cites arXiv preprint arXiv:2604.01411 , year=.

Understanding Reasoning from Pretraining to Post-Training arXiv preprint arXiv:2604.01411 , year=

Reference 39

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source=arxiv_source observed=2026-08-01T21:26:34.855268Z digest=sha256:0a04b5e5e1e4b36d545afa0c280ea389f97e336235c10b00bc25f340a0a77c6b

Observation 9ab0fc64-d5c4-4525-b062-90ff395db5a3 · outbound

This paper cites arXiv preprint arXiv:2503.19551 , year=.

Understanding Reasoning from Pretraining to Post-Training arXiv preprint arXiv:2503.19551 , year=

Reference 40

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no resolver link, observed 2026-08-01T21:26:34.944396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:26:34.944396Z digest=sha256:86b67c7c3abd6095abfcda594aef6f06df7bfbb60d75816b706679b59d031ba1

Observation e1aa124e-f5a7-40f8-8bbb-47722f4c3f60 · outbound

This paper cites arXiv preprint arXiv:2603.12151 , year=.

Understanding Reasoning from Pretraining to Post-Training arXiv preprint arXiv:2603.12151 , year=

Reference 41

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unresolved
no resolver link, observed 2026-08-01T21:26:35.036633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:26:35.036633Z digest=sha256:e2191b637009df1c0791ae5a09b59822e175dd63d3252f5982215ad3bc289509

Observation 4785bc8e-996f-4b65-a777-71c970f5b7cc · outbound

This paper cites an unresolved cited work.

Understanding Reasoning from Pretraining to Post-Training Unresolved cited work

Reference 42

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unresolved
no resolver link, observed 2026-08-01T21:26:35.100440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:26:35.100440Z digest=sha256:7fa3ed06346c0b779caf56766eb74f1e9cdc6cd4cdbf55ffda20df73d5841164

Observation 5b9ac02a-dbd0-464c-a7fa-f04b92ac1b3f · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Understanding Reasoning from Pretraining to Post-Training Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 43

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unresolved
no resolver link, observed 2026-08-01T21:26:35.191672Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T21:26:35.191672Z digest=sha256:3f495270adf02fb902290076551b02724901b5cb0816ebdb421bb178a183668c

Observation 9d0ee7bb-462d-4f8d-b77c-7d7be8780496 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

Understanding Reasoning from Pretraining to Post-Training DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 44

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unresolved
no resolver link, observed 2026-08-01T21:26:35.256751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:26:35.256751Z digest=sha256:e51b69676a07a86ab3630c53c5641618a320296fd95898a2618718a9ed2e57b8

Observation 3e830194-4084-4a75-8762-4b6451a1e9db · outbound

This paper cites SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild.

Understanding Reasoning from Pretraining to Post-Training SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild

Reference 45

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unresolved
no resolver link, observed 2026-08-01T21:26:35.371952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:26:35.371952Z digest=sha256:0f4791833075a6c29e2e2eda42e36de8c9ffae7dfb9a763c30fdd864a5b4c52a

Observation 0efc0bd5-37b3-490e-86aa-af80a7317620 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Understanding Reasoning from Pretraining to Post-Training DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 46

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unresolved
no resolver link, observed 2026-08-01T21:26:35.468782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:26:35.468782Z digest=sha256:9e3286f5f9aed268a69d0a3b95e2bbdfb10f31d58b8c28c92e8c83269a8e16e9

Observation 473d8c2d-476f-4065-836f-32d1657426be · outbound

This paper cites Google AI , volume=.

Understanding Reasoning from Pretraining to Post-Training Google AI , volume=

Reference 47

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no resolver link, observed 2026-08-01T21:26:35.533985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:26:35.533985Z digest=sha256:ad24c8fd71ce4777210e0e4cb7bdf0aadc3d534dcb5d80f91165d5338cc340a3

Observation 84f78f46-bfb5-49b4-852a-90d2f2a76c47 · outbound

This paper cites nature , volume=.

Understanding Reasoning from Pretraining to Post-Training nature , volume=

Reference 48

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no resolver link, observed 2026-08-01T21:26:35.635555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:26:35.635555Z digest=sha256:12530b7445bd638ae6b0ea087bfa05ff21ebfe1083768adf5bcd0104d0bac97c

Observation 6e532969-9a8e-4aa0-953d-7b2c4afde200 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Understanding Reasoning from Pretraining to Post-Training Advances in Neural Information Processing Systems , volume=

Reference 49

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no resolver link, observed 2026-08-01T21:26:35.793794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:26:35.793794Z digest=sha256:06cc8c1684181bce007166ff7dbe65a5162a905e6953567c4fb4b75fad63f826

Observation 27fc059a-610b-4a7b-897f-6a6bfd8f15ce · outbound

This paper cites Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision.

Understanding Reasoning from Pretraining to Post-Training Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

Reference 50

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no resolver link, observed 2026-08-01T21:26:35.909813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:26:35.909813Z digest=sha256:b531964b6c20050f00484c2eec33154db435328eee4cb70126bd90fe6b1e2655

Observation 7fa24bc0-fc18-4e03-b808-19433a53a2e6 · outbound

This paper cites Nemotron-CC-Math: A 133 Billion-Token-Scale High Quality Math Pretraining Dataset.

Understanding Reasoning from Pretraining to Post-Training Nemotron-CC-Math: A 133 Billion-Token-Scale High Quality Math Pretraining Dataset

Reference 51

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no resolver link, observed 2026-08-01T21:26:36.017309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:26:36.017309Z digest=sha256:6a55c29e79f96c1d160b078558d4f9eaf80fd061e477a90e174e8fbbd2de756f

Pith citing papers

No inbound Pith citation observations are available.