Paper Citation Record · LEDGER

State2State: Environment-Derived Mid-Training for LLM Agents

As of 18 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2608.04934.

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

pith.paper-citation-record.v1
2608.04934 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:40:40.747744Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

13 of 13 outbound references displayed

verified exact0
verified fuzzy2
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bc41c385-6f6e-45ac-9c27-505fb56a10a5 · outbound

This paper cites Tongyi DeepResearch Technical Report.

State2State: Environment-Derived Mid-Training for LLM Agents Tongyi DeepResearch Technical Report

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T14:40:40.696250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8d34a17-fff4-44e3-9407-bdd10225ef3b · outbound

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

State2State: Environment-Derived Mid-Training for LLM Agents DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T14:40:40.700383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3861aa21-7c54-4201-ad20-470a8422aa3d · outbound

This paper cites InProceedings of the 2025 Con- ference on Empirical Methods in Natural Language Processing, EMNLP 2025, Suzhou, China, November 4-9, 2025, pages 3062–3077.

State2State: Environment-Derived Mid-Training for LLM Agents InProceedings of the 2025 Con- ference on Empirical Methods in Natural Language Processing, EMNLP 2025, Suzhou, China, November 4-9, 2025, pages 3062–3077

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T14:40:40.708919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0724f0aa-8893-44af-aac7-f7f83ed2056c · outbound

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

State2State: Environment-Derived Mid-Training for LLM Agents DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T14:40:40.713363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a8f32d7-f285-45a4-8f2c-e24f7d06f64b · outbound

This paper cites action":.

State2State: Environment-Derived Mid-Training for LLM Agents action":

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:40:40.950891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 40f084a9-40bb-4e2c-be14-a26ce8e07740 · outbound

This paper cites an unresolved cited work.

State2State: Environment-Derived Mid-Training for LLM Agents Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-15T14:40:40.975416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d0910b67-e55f-4904-b2ee-ee43266a8ae8 · outbound

This paper cites an unresolved cited work.

State2State: Environment-Derived Mid-Training for LLM Agents Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-15T14:40:40.963226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 63362e1e-7064-48c6-88f6-99ab04cd2bb6 · outbound

This paper cites an unresolved cited work.

State2State: Environment-Derived Mid-Training for LLM Agents Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-15T14:40:40.937890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8892b842-9d66-4b21-81b7-05dd321e4cd1 · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

State2State: Environment-Derived Mid-Training for LLM Agents Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 507

Resolution: unresolved; no resolver link, observed 2026-08-15T14:40:40.691781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a65e4dc-bf5c-406a-abc7-93b0e57f9905 · outbound

This paper cites OpenAI GPT-5 System Card.

State2State: Environment-Derived Mid-Training for LLM Agents OpenAI GPT-5 System Card

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-15T14:40:40.704545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a8c715e-901a-4306-ac77-8a187d70b1ab · outbound

This paper cites action":.

State2State: Environment-Derived Mid-Training for LLM Agents action":

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:40:40.988210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e857b4fd-b8e9-4c3d-9b9b-dde89460a76d · outbound

This paper cites Group-in-Group Policy Optimization for LLM Agent Training.

State2State: Environment-Derived Mid-Training for LLM Agents Group-in-Group Policy Optimization for LLM Agent Training

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-15T14:40:40.686820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09c0c3c2-cc7e-4e5c-9b72-92da381eef3d · outbound

This paper cites an unresolved cited work.

State2State: Environment-Derived Mid-Training for LLM Agents Unresolved cited work

Reference 3077

Resolution: unresolved; no resolver link, observed 2026-08-15T14:40:40.717476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.