Paper Citation Record · LEDGER

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models

As of 10 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2506.07463.

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

pith.paper-citation-record.v1
2506.07463 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:41:14.636513Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

40 of 40 outbound references displayed

verified exact0
verified fuzzy20
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1bb2cb67-650b-4bc9-bbeb-2e6be8b0b00d · outbound

This paper cites Rethinking reflection in pre-training, 2025.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Rethinking reflection in pre-training, 2025

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:15.061372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ea004250-d416-4924-ade8-c31ed815c17a · outbound

This paper cites COIG-CQIA: Quality is All You Need for Chinese Instruction Fine-tuning.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models COIG-CQIA: Quality is All You Need for Chinese Instruction Fine-tuning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.511955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 761eba16-ca57-421d-bf7b-81fca97c88fa · outbound

This paper cites Careful selection of knowledge to solve open book question answering.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Careful selection of knowledge to solve open book question answering

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:15.052572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5ffeffb1-d8a8-400a-bdcc-4bd59c1a7ac4 · outbound

This paper cites CCI-Data [Data set].

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models CCI-Data [Data set]

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:15.042870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0db9bfae-f766-41b9-963b-b303ddd72d8b · outbound

This paper cites CCI2-Data [Data set].

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models CCI2-Data [Data set]

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:15.032842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 821bc742-0f46-4d42-ab6c-093a5f3eb79b · outbound

This paper cites WuDaoCorporaText [Data set].

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models WuDaoCorporaText [Data set]

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:15.022976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a77e3deb-fb75-4756-be2c-09d6d7bc5a95 · outbound

This paper cites Piqa: Reasoning about physical commonsense in natural language, 2019.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Piqa: Reasoning about physical commonsense in natural language, 2019

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.527577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c76ddd3f-3f49-4c0c-bd78-aa2c8867756a · outbound

This paper cites an unresolved cited work.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:41:15.007881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation eb896623-f4b0-4fca-92b1-f8139b77609c · outbound

This paper cites Data- juicer: A one-stop data processing system for large language models.Companion of the 2024 International Conference on Management of Data, 2023.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Data- juicer: A one-stop data processing system for large language models.Companion of the 2024 International Conference on Management of Data, 2023

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.999494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6016aaf2-4ce7-44a1-a002-f5a9d56d1b65 · outbound

This paper cites Chinesewebtext: Large-scale high-quality chinese web text extracted with effective evaluation model, 2023.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Chinesewebtext: Large-scale high-quality chinese web text extracted with effective evaluation model, 2023

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.990030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1b0e76a6-13b4-4204-baec-7bb14c2f216c · outbound

This paper cites Think you have solved question answering? try arc, the ai2 reasoning challenge, 2018.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Think you have solved question answering? try arc, the ai2 reasoning challenge, 2018

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.539286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e138668-d626-46a3-9a64-3ba295c84ae2 · outbound

This paper cites Unsupervised Cross-lingual Representation Learning at Scale.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Unsupervised Cross-lingual Representation Learning at Scale

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.542023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d71b92f-79bb-419f-ae51-fcffb048db63 · outbound

This paper cites Zhang, Han Bao, Hanwei Xu, Haocheng Wang, Haowei Zhang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Li, Hui Qu, J.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Zhang, Han Bao, Hanwei Xu, Haocheng Wang, Haowei Zhang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Li, Hui Qu, J

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.975953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 61725105-411f-4f92-a3ee-38d037407545 · outbound

This paper cites Lighteval: A lightweight framework for llm evaluation, 2023.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Lighteval: A lightweight framework for llm evaluation, 2023

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.965967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 491272bb-96a7-46ad-990d-94452d443c50 · outbound

This paper cites Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.552614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eedb7d1d-8808-4cc4-afce-714e6be0fb58 · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.555798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 568e34bd-b5b9-4742-a8e1-d580cb3dea04 · outbound

This paper cites Wanjuan: A comprehensive multimodal dataset for advancing english and chinese large models, 2023.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Wanjuan: A comprehensive multimodal dataset for advancing english and chinese large models, 2023

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.956085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 124c3a16-07df-4d3c-9311-ab3121e7cefe · outbound

This paper cites Measuring massive multitask language understanding, 2021.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Measuring massive multitask language understanding, 2021

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.562041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21ec9a21-6c4c-414c-a150-2e4b90653a8e · outbound

This paper cites C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.565274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a95f47b-695d-4749-9c5a-66e148574b86 · outbound

This paper cites Bag of Tricks for Efficient Text Classification.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Bag of Tricks for Efficient Text Classification

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.568240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d10ba18-7116-4154-add2-7ca26760cf8e · outbound

This paper cites Deduplicating training data makes language models better, 2022.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Deduplicating training data makes language models better, 2022

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.571434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation adeb30bd-1aff-4068-a773-356b85376e54 · outbound

This paper cites Levesque, Ernest Davis, and Leora Morgenstern.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Levesque, Ernest Davis, and Leora Morgenstern

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.930480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f4787769-6224-46fb-bbf7-6ecd8ae82858 · outbound

This paper cites Cmmlu: Measuring massive multitask language understanding in chinese, 2024.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Cmmlu: Measuring massive multitask language understanding in chinese, 2024

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.921385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation eecd1c91-24f1-4d04-af7c-e816aa38a308 · outbound

This paper cites Datacomp-lm: In search of the next generation of training sets for language models, 2024.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Datacomp-lm: In search of the next generation of training sets for language models, 2024

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.912583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5a40faad-a015-4d50-b153-f5e2fc448e83 · outbound

This paper cites Openhermes 2.5-zh: A partial chinese translation of openhermes-2.5, 2024.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Openhermes 2.5-zh: A partial chinese translation of openhermes-2.5, 2024

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.903381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f80f6c1e-32d9-412a-82e4-9f296db90657 · outbound

This paper cites Fineweb2: A sparkling update with 1000s of languages, December 2024.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Fineweb2: A sparkling update with 1000s of languages, December 2024

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.894325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 170dd499-10b3-44f6-a796-c6a1bb4bd353 · outbound

This paper cites The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.588446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec09a55b-c1db-4934-9655-83e2df2b2ec1 · outbound

This paper cites Deduplicate Text Datasets.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Deduplicate Text Datasets

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.884898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0bee756a-db61-495c-b69a-e91352b8ca2b · outbound

This paper cites Socialiqa: Com- monsense reasoning about social interactions, 2019.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Socialiqa: Com- monsense reasoning about social interactions, 2019

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.596279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edbe1d46-58dd-4497-939c-f4d2edd9d3f6 · outbound

This paper cites Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.600683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae53137f-0530-4d27-a82b-da4d9d9ba88d · outbound

This paper cites Nemotron-cc: Transforming common crawl into a refined long-horizon pretraining dataset, 2024.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Nemotron-cc: Transforming common crawl into a refined long-horizon pretraining dataset, 2024

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.788616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d4c02cd1-5746-45b0-9ac3-8b0cc7ddabc6 · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.610652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ff8f4b7-0c07-4cd2-83bb-0dc2b5b4905b · outbound

This paper cites Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.613803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62abf318-fd8f-4daf-bd0b-cb4e3abf1b12 · outbound

This paper cites Qwen2.5: A party of foundation models, September 2024.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Qwen2.5: A party of foundation models, September 2024

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.616833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfb42c5d-8ef1-4ffb-a744-bcb6f04f7312 · outbound

This paper cites Cci3.0-hq: a large-scale chinese dataset of high quality designed for pre-training large language models, 2024.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Cci3.0-hq: a large-scale chinese dataset of high quality designed for pre-training large language models, 2024

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.773012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ee8c4ba0-2457-4119-97b4-aa53e8736227 · outbound

This paper cites Qwen2 Technical Report.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Qwen2 Technical Report

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.622934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fec69a07-0e43-46e1-91ea-2e38f3306176 · outbound

This paper cites Opencsg chinese corpus: A series of high-quality chinese datasets for llm training, 2025.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Opencsg chinese corpus: A series of high-quality chinese datasets for llm training, 2025

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.763329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 094a470d-2194-4559-bdd4-ab9441d562f3 · outbound

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

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:14.629752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 730a1797-7f91-41a9-a855-48e534836ef8 · outbound

This paper cites Games" and.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Games" and

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:14.753261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 02d8a56d-45ad-4bdd-ac3c-98ac11d90f2d · outbound

This paper cites an unresolved cited work.

CCI4.0: A Bilingual Pretraining Dataset for Enhancing Reasoning in Large Language Models Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:41:14.743827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.