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Paper Citation Record · LEDGER

AWorld: Orchestrating the Training Recipe for Agentic AI

As of 5 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 6 inbound Pith citation observations for arXiv:2508.20404.

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

pith.paper-citation-record.v1
2508.20404 v2

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:10:17.811779Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T19:59:47.108021Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T00:19:16.795480Z

Reference resolution

12 of 12 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b4757a87-7b08-4f27-8cb1-9c335fe12403 · outbound

This paper cites GPT-4 Technical Report.

AWorld: Orchestrating the Training Recipe for Agentic AI GPT-4 Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.767118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.767118Z digest=sha256:b0e51688ebd7a164e4517fb94117e73e8a480f56fedc2e9f82a94a81d0195c8a

Observation 133c92d6-9fc2-484b-9c28-6f7fac1cd17f · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

AWorld: Orchestrating the Training Recipe for Agentic AI Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.775534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.775534Z digest=sha256:653fcaa76f3c383bff45021b0b02bf25ca94bce607d566d9c12d18afdbe8b460

Observation 0525c134-88c7-4d1a-a5e2-4c201a03f947 · outbound

This paper cites AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning.

AWorld: Orchestrating the Training Recipe for Agentic AI AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.779979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.779979Z digest=sha256:c46dcd9f2ac60afd8a56371cfd6587ca6bd8362f2b8c1a598eccab8f27b1b2a9

Observation 75fbe60a-e61f-479d-845a-63f3aaabcb31 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

AWorld: Orchestrating the Training Recipe for Agentic AI Gemini: A Family of Highly Capable Multimodal Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.784190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.784190Z digest=sha256:92aa940da44853afb4fe887b4116edf9dedeef5b04b7d70181bfe9924f2f53b1

Observation 45528391-3a99-4dd9-a7d7-098572d032dc · outbound

This paper cites DeepSeek-V3 Technical Report.

AWorld: Orchestrating the Training Recipe for Agentic AI DeepSeek-V3 Technical Report

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.796330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.796330Z digest=sha256:86ba4cc4afa98cc592b757a4db7949eb98c73b1b02fc482e12c5f43f6c3fb67b

Observation d2f41bad-0e7e-48a7-a8c1-cb46593192a9 · outbound

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

AWorld: Orchestrating the Training Recipe for Agentic AI DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.803448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.803448Z digest=sha256:12e237042342aa1a3d58741e7c533bd6317b26b24107c7394d72c8c4cc01910e

Observation feb7142d-a566-442a-9801-5c560cbeafb6 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

AWorld: Orchestrating the Training Recipe for Agentic AI LLaMA: Open and Efficient Foundation Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.807085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.807085Z digest=sha256:5933f0b5453d9224633cfeccb86bf0fdfc24a204f2c965af82d5b84028fe8656

Observation 3238b2b1-c95a-49c1-b94a-ef7ba5aeef1b · outbound

This paper cites Qwen3 Technical Report.

AWorld: Orchestrating the Training Recipe for Agentic AI Qwen3 Technical Report

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.811779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.811779Z digest=sha256:06fe4530cd71b49aaa4fdc3f8de877a77f8764e562e298e59d7b49638b59a82c

Observation 4ca00504-e797-474e-be25-0fe8fea63d1b · outbound

This paper cites Ai agents vs.

AWorld: Orchestrating the Training Recipe for Agentic AI Ai agents vs

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.799977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.799977Z digest=sha256:5d0a168dac68e79b69384d65c95631fe0df80572089d9733a56d2de511c738ed

Observation 5c68fa08-364a-47e6-a737-f71a0149f621 · outbound

This paper cites OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework.

AWorld: Orchestrating the Training Recipe for Agentic AI OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.788181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.788181Z digest=sha256:b1054913ff3a99f6f605e215e6e4e7b29d3706b83c67762ff954b0f1a5798c9a

Observation e667310a-5dd0-4317-9218-674d2a6bbeb9 · outbound

This paper cites GPT-4o System Card.

AWorld: Orchestrating the Training Recipe for Agentic AI GPT-4o System Card

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.792251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.792251Z digest=sha256:038a43bab0358e9d29328baf5cf9284ba88df4f0a1ef7efc214f7f0aba23a96b

Observation 505f5e59-ca11-4c3d-be44-4e771bcccba8 · outbound

This paper cites xbench: Tracking Agents Productivity Scaling with Profession-Aligned Real-World Evaluations.

AWorld: Orchestrating the Training Recipe for Agentic AI xbench: Tracking Agents Productivity Scaling with Profession-Aligned Real-World Evaluations

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-05T15:10:17.771453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:10:17.771453Z digest=sha256:775521d817978ac2275136c5fef2fb2374aeac1540b85c0ab11e119c8ae5f093

Pith citing papers

Observation aeb91813-9a35-4e33-b48b-98c407525b3e · inbound

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey cites this paper.

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey AWorld: Orchestrating the Training Recipe for Agentic AI

Reference 288

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:48.808584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-18T19:19:36.427337Z digest=sha256:408ff5b8886d491fbe16646ba526419ee00a3078c4bbd471e33a49e81558a07c

Observation bfa15bd4-93ee-4c12-b978-6e9837d9ad28 · inbound

DIG to Heal: Scaling General-purpose Agent Collaboration via Explainable Dynamic Decision Paths cites this paper.

DIG to Heal: Scaling General-purpose Agent Collaboration via Explainable Dynamic Decision Paths AWorld: Orchestrating the Training Recipe for Agentic AI

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-02T19:59:47.108021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T19:59:47.108021Z digest=sha256:3733342fd38613e93669bf931dfad0ef2504eabfc2987b9a016ba1f986c74af7

Observation 014aeef6-ea93-4bfc-982e-3b98f310fe13 · inbound

Open, Reliable, and Collective: A Community-Driven Framework for Tool-Using AI Agents cites this paper.

Open, Reliable, and Collective: A Community-Driven Framework for Tool-Using AI Agents AWorld: Orchestrating the Training Recipe for Agentic AI

Reference 47

Resolution
unresolved
no resolver link, observed 2026-07-14T19:59:59.030585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T19:59:59.030585Z digest=sha256:c0d6af9d6bf01b44cfc59e0c019c54d2e3c879aa86d120d17494ba4d25a4a15a

Observation 20c8cad9-2896-4950-a6b2-234cb0d0fc21 · inbound

Autogenesis: A Self-Evolving Agent Protocol cites this paper.

Autogenesis: A Self-Evolving Agent Protocol AWorld: Orchestrating the Training Recipe for Agentic AI

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-10T10:29:24.726341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T10:27:34.143483Z digest=sha256:18e4e1f781a66644ba98cd0ca6ce4304b6d2481f75b0244a7aa3c5246e81bdcf

Observation 71948c83-6bec-4603-bac2-9add268f273b · inbound

Autogenesis: A Self-Evolving Agent Protocol cites this paper.

Autogenesis: A Self-Evolving Agent Protocol AWorld: Orchestrating the Training Recipe for Agentic AI

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-21T00:19:16.799123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-21T00:15:18.079458Z digest=sha256:3a7ec3a347e358de9069d1c5f0ab6e82b482fe860691e3c045c6ce02ee96be7c

Observation 349415dc-b4bc-433a-bb62-9e139d99eb42 · inbound

OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction cites this paper.

OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction AWorld: Orchestrating the Training Recipe for Agentic AI

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T23:41:20.289348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-07T16:23:36.888399Z digest=sha256:8de6e590c198310c1e34e71822d19de6ed8ea3ef879fa59bd92c7c615da8dfb0