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Paper Citation Record · LEDGER

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training

As of 5 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2607.16257.

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

pith.paper-citation-record.v1
2607.16257 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T09:45:49.665576Z

measured 29 of 29 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 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

29 of 29 outbound references displayed

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External citation measurements

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Outbound references

Observation f114d361-add9-4ea6-a055-b6a0b6bc87b7 · outbound

This paper cites REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization

Reference 3

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Observation d96548a6-2f08-45e0-a554-333d234194e3 · outbound

This paper cites A Survey on Large Language Model-Based Game Agents.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training A Survey on Large Language Model-Based Game Agents

Reference 4

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source=pdf_text observed=2026-08-02T09:45:49.548413Z digest=sha256:16dc798dedc732614ab0fead282bc2fcd34710610ab769dd7a5301b17c51049b

Observation 6a7d3ae8-eeaf-4855-958e-11c89f6d6b4b · outbound

This paper cites OpenAI o1 System Card.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training OpenAI o1 System Card

Reference 5

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Observation ba5d6b48-4691-4b86-99e8-66df3c35fabb · outbound

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

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 6

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Observation 20f932c5-e23c-4d12-bf13-d43e33f49ba3 · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 7

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source=pdf_text observed=2026-08-02T09:45:49.562419Z digest=sha256:5da73cf40be0fdbab50808b6d32a8460f77d9ad1d8cec2bea052299de9636666

Observation 9d567aa5-be18-4a84-afc7-17334a4ea033 · outbound

This paper cites GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents

Reference 9

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Observation d8072b01-5ff9-4ae2-b0f2-9a7d00c28c66 · outbound

This paper cites From Reasoning to Code: GRPO Optimization for Underrepresented Languages.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training From Reasoning to Code: GRPO Optimization for Underrepresented Languages

Reference 11

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Observation 4055e064-4f29-42cc-b94e-449dfbbec35f · outbound

This paper cites Adapt: As-needed decompo- sition and planning with language models.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training Adapt: As-needed decompo- sition and planning with language models

Reference 12

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Observation dc122ef0-c6d1-4017-8f4d-9b4c54bf670f · outbound

This paper cites A., and Lewis, M.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training A., and Lewis, M

Reference 13

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Observation be1a788c-6562-43b2-89f4-218ee59d5c37 · outbound

This paper cites Qwen2.5 Technical Report.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training Qwen2.5 Technical Report

Reference 14

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source=pdf_text observed=2026-08-02T09:45:49.593092Z digest=sha256:7545da1374b945c43f2452647bd2c94dae4d1d00be647936343982dfa52c3cf4

Observation 313da221-8f45-4d14-b924-9fa21835b6d6 · outbound

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

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 15

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source=pdf_text observed=2026-08-02T09:45:49.597133Z digest=sha256:40abbe59a89f466f9e282cf953053428051ec4ea51ee18ebb868ece54bd2d7bd

Observation cd6c5b9b-c9c2-421b-962b-f0f5f56503ae · outbound

This paper cites ZeroSearch: Incentivize the Search Capability of LLMs without Searching.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 16

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Observation 201aacc8-872c-42c7-9d8e-6006877df8f3 · outbound

This paper cites Simpletir: End-to-end reinforcement learning for multi-turn tool-integrated reasoning.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training Simpletir: End-to-end reinforcement learning for multi-turn tool-integrated reasoning

Reference 19

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Observation 30bd35b0-5d8f-47b4-820b-8998ed61cd80 · outbound

This paper cites an unresolved cited work.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training Unresolved cited work

Reference 20

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Observation 6477b146-22e0-4b29-84b7-91020de15fca · outbound

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

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training The Landscape of Agentic Reinforcement Learning for LLMs: A Survey

Reference 21

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Observation c25d05f8-59e8-4e7c-8b30-ae901b57b9b2 · outbound

This paper cites and Zhang, A.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training and Zhang, A

Reference 22

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Observation 09e75ab7-187a-4056-81d8-d5629d1447ac · outbound

This paper cites doi: 10.18653/v1/2024.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training doi: 10.18653/v1/2024

Reference 23

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source=pdf_text observed=2026-08-02T09:45:49.630037Z digest=sha256:5d29b6a3df441d7c9c6eabc29d1d591a9341cbf730dc2b7aa43461b759ebcc97

Observation 8cc84f77-a5f7-4edb-8c98-553b685facf8 · outbound

This paper cites making-of.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training making-of

Reference 24

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source=pdf_text observed=2026-08-02T09:45:49.634091Z digest=sha256:7628efa5a1def60aae580164ba9beb3a653da37f2aa5b7b5f2fb6761d9cf6813

Observation db2481b3-ccec-44a0-a7b1-cc4bcf4cb9e0 · outbound

This paper cites making-of.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training making-of

Reference 26

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Observation 4b7ed04b-be6e-4d6f-92b4-9edf4f7450f4 · outbound

This paper cites making-of.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training making-of

Reference 28

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Observation f797b167-8465-40c4-b821-4973b3bccf4a · outbound

This paper cites making-of.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training making-of

Reference 30

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Observation eb2a3f79-5d92-49af-9a5a-f1e825255ae9 · outbound

This paper cites Therefore, the answer is.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training Therefore, the answer is

Reference 31

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Observation d67c3502-94fd-48e4-ac78-d705b89928e7 · outbound

This paper cites Therefore, the answer is 1982.< /think> <answer>1982< /answer> (As = +0.377) User:Congratulations! You have answered the question correctly!!! 21.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training Therefore, the answer is 1982.< /think> <answer>1982< /answer> (As = +0.377) User:Congratulations! You have answered the question correctly!!! 21

Reference 32

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Observation b6a23d0b-ff2c-4156-9c67-44fa9a8e2822 · outbound

This paper cites RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning

Reference 2008

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Observation 5ac0cc34-16d4-49af-b040-5518247ae594 · outbound

This paper cites LAVA: Data Valuation without Pre-Specified Learning Algorithms.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training LAVA: Data Valuation without Pre-Specified Learning Algorithms

Reference 2017

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Observation 763e6f28-3062-4056-96fa-b9052d9b42fb · outbound

This paper cites AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning

Reference 2018

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Observation cbbb27ec-3774-42fd-8c84-f3db1cfc6e06 · outbound

This paper cites When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories

Reference 2023

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Observation a74b787b-e60c-4ba7-88e0-0eee59648c1b · outbound

This paper cites Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps

Reference 2024

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Observation 0812fa76-c88c-4290-9848-71d20c002f2b · outbound

This paper cites FireAct: Toward Language Agent Fine-tuning.

From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training FireAct: Toward Language Agent Fine-tuning

Reference 2025

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Pith citing papers

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