Paper Citation Record · LEDGER

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels

As of 7 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2510.06499.

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

pith.paper-citation-record.v1
2510.06499 v2

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-18T08:39:54.747656Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

14 of 14 outbound references displayed

verified exact9
verified fuzzy3
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 73657560-8860-486f-b566-08c91ad64deb · outbound

This paper cites Mmlu-pro: A more robust and challenging multi-task language under- standing benchmark.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels Mmlu-pro: A more robust and challenging multi-task language under- standing benchmark

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T08:41:09.350053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4843b6e9-6fb5-4766-9fb6-83d60f140e3b · outbound

This paper cites Redpajama: an open dataset for training large language models.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels Redpajama: an open dataset for training large language models

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T08:41:09.353492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3d078f5f-a8a0-4351-aadb-4ad72df21172 · outbound

This paper cites SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-18T08:41:08.353287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d20d0a03-a512-4361-babe-7be14fa90ff2 · outbound

This paper cites QuRating: Selecting High-Quality Data for Training Language Models.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels QuRating: Selecting High-Quality Data for Training Language Models

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T08:41:08.344219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0bb9845d-73aa-4314-a9ec-3e8cadbf3b4f · outbound

This paper cites [Online].

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels [Online]

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T08:41:09.345872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 40741bdb-1d0d-43a4-b460-8705c21db40a · outbound

This paper cites Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-18T08:41:08.312945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 738d2395-8ced-492f-8188-a3ea26785b82 · outbound

This paper cites Qwen2.5 Technical Report.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels Qwen2.5 Technical Report

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-18T08:41:08.359669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 466472d6-e19a-43b4-b170-81f20f369d59 · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-18T08:41:08.330839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ceff8fe6-8ee9-4414-b8ed-4b4bb7f0dd43 · outbound

This paper cites Naturalreasoning: Reasoning in the wild with 2.8 m challenging questions.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels Naturalreasoning: Reasoning in the wild with 2.8 m challenging questions

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-18T08:41:08.325104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 975deb2d-d305-485c-aafe-4dac78aed692 · outbound

This paper cites Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-18T08:41:08.376353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6a2fa7a9-9b77-4d60-865b-50ae03e35d12 · outbound

This paper cites Nemotron-Research-Tool-N1: Exploring Tool-Using Language Models with Reinforced Reasoning.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels Nemotron-Research-Tool-N1: Exploring Tool-Using Language Models with Reinforced Reasoning

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-18T08:41:08.319271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c618ce7f-71c6-448d-adf0-0207f780b669 · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-18T08:41:08.337290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b14b2432-90c1-4405-9633-41bacbf3e64a · outbound

This paper cites Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T08:41:08.306680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation eb87b5fe-d310-4f5a-af58-ca3f21acf98a · outbound

This paper cites MegaMath: Pushing the Limits of Open Math Corpora.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels MegaMath: Pushing the Limits of Open Math Corpora

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-18T08:41:08.385978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

No inbound Pith citation observations are available.