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Paper Citation Record · LEDGER

Global Optimization and Inference-Time Region Grafting for Agentic Workflows

As of 9 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2608.02353.

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

pith.paper-citation-record.v1
2608.02353 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T08:52:24.632934Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

21 of 21 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved21
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 569e0ff6-d78a-4d62-b290-4072918247d6 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows Evaluating Large Language Models Trained on Code

Reference 3

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no resolver link, observed 2026-08-04T08:52:21.634519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:21.634519Z digest=sha256:643da37aac99b090f019895aa61e2e04bd396609c97beedf69a0748974e63669

Observation 9da1ec30-dc35-43fe-ae53-cc052cdd7033 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows Training Verifiers to Solve Math Word Problems

Reference 5

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T08:52:21.880653Z digest=sha256:c48c6171f7130a713ab7f80fcb6019e344bc4ca1010eea0508c3b2ea673e65cc

Observation 746d44c9-e417-4695-abdd-0794370ff34b · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:22.058758Z digest=sha256:857c7e8c2d5acd860eef496f02231ab949a6864adc25005e853a15fc62174e73

Observation fe9df4b3-0278-448c-942d-e2a15f5666b3 · outbound

This paper cites CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society

Reference 10

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no resolver link, observed 2026-08-04T08:52:22.517554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:22.517554Z digest=sha256:ab53021eb0de04c3cbc1910a55b8932bddcb69903dcd4b5d26ea850267b8d9e3

Observation 30c7ed1b-d96a-45b1-8cbe-4e79ba477902 · outbound

This paper cites arXiv:2506.06017.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows arXiv:2506.06017

Reference 11

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no resolver link, observed 2026-08-04T08:52:22.654776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:22.654776Z digest=sha256:ec5284477b1ceac4080e6f12a156b247f607cb6331d8d3b7757c8512091aaf76

Observation e535defa-42a1-4ad4-84c3-245379a10425 · outbound

This paper cites LLM+P: Empowering Large Language Models with Optimal Planning Proficiency.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Reference 12

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no resolver link, observed 2026-08-04T08:52:22.773150Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:22.773150Z digest=sha256:23bc4996c8073cca459104bf17d63f717efaf136548ee42bb1cd11cf715aa8ba

Observation 3ca042bf-0a89-4c78-86cf-3a76a0c91882 · outbound

This paper cites A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration

Reference 13

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no resolver link, observed 2026-08-04T08:52:22.942819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:22.942819Z digest=sha256:d7dd4779cb1de370c3e8f532ff48e2f070ccf650446da5d748fd5661a7f4ee3d

Observation 49385e71-aeb2-465c-b170-8ef4c70b5d6d · outbound

This paper cites Large Language Models: A Survey.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows Large Language Models: A Survey

Reference 14

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no resolver link, observed 2026-08-04T08:52:23.152337Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:23.152337Z digest=sha256:d1431631c106a2cb101a729b791b31e85b888e836b5b2f50e3361690422724a9

Observation 8b24dafd-6844-4bae-a4fd-0b780ab5b5fd · outbound

This paper cites Flow: Modularized Agentic Workflow Automation.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows Flow: Modularized Agentic Workflow Automation

Reference 15

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no resolver link, observed 2026-08-04T08:52:23.399703Z

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source=pdf_text observed=2026-08-04T08:52:23.399703Z digest=sha256:e76ed0e948f89200e29fca4388cf5991a05e5497690ed83f95cced4c35fa8f5e

Observation 569120ef-8cd5-4a0a-bfb9-f355b732e2c1 · outbound

This paper cites AgentSquare: Automatic LLM Agent Search in Modular Design Space.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows AgentSquare: Automatic LLM Agent Search in Modular Design Space

Reference 16

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no resolver link, observed 2026-08-04T08:52:23.570960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:23.570960Z digest=sha256:a0cf3eced305116b0dbbd23cf7975bfc4b3b3699d535ccecf1ee718a3fb04f75

Observation a90bbd73-fb12-43ce-a7fe-ab71ee2794cd · outbound

This paper cites InInternational Conference on Learning Representations (ICLR).

Global Optimization and Inference-Time Region Grafting for Agentic Workflows InInternational Conference on Learning Representations (ICLR)

Reference 17

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no resolver link, observed 2026-08-04T08:52:23.741422Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:23.741422Z digest=sha256:39dae907b948265114c6c7312e54e314bb1ac5c22d6d367c9ee9656c29a920d2

Observation c530f464-9e02-4f9f-8422-1b62789c73e6 · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 19

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no resolver link, observed 2026-08-04T08:52:24.170202Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:24.170202Z digest=sha256:5bdab5d82e92f4b6f61f3cfbd7b4ceb79c13ea1f429e14e2413ad71a3d152345

Observation e7e3fbb0-2131-45f0-8f88-c6911019cb21 · outbound

This paper cites A Survey of Large Language Models.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows A Survey of Large Language Models

Reference 21

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no resolver link, observed 2026-08-04T08:52:24.632934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:24.632934Z digest=sha256:e3345c4b6543408ae1cbc66970cd87dfeba20f0e6eb89c8d6cde222245abc2c8

Observation f1c06da2-4a10-41fc-bb93-7d34d01ab07a · outbound

This paper cites In Sarkar, V.; Ryder, B.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows In Sarkar, V.; Ryder, B

Reference 1994

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no resolver link, observed 2026-08-04T08:52:22.391046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:22.391046Z digest=sha256:b7c4b7b90d0a6ef698f564b0d447bdf1823f8c799d232bd35b81559d9fd7fb3e

Observation ca8a4d47-fa27-4cad-85fb-05c9398795aa · outbound

This paper cites Why Do Multi-Agent LLM Systems Fail?.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows Why Do Multi-Agent LLM Systems Fail?

Reference 2012

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no resolver link, observed 2026-08-04T08:52:21.501302Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:21.501302Z digest=sha256:e987f4554210db118df8683df85b71904bdd8afc80e955d5467557fa14adce12

Observation 1eed0e35-3bac-4ac3-bdce-9067b5658b55 · outbound

This paper cites Program Synthesis with Large Language Models.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows Program Synthesis with Large Language Models

Reference 2021

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:21.436132Z digest=sha256:c30ed761e863c2e4cb5fa21af289298a74e0245d0dcdff4370cf772958d87fc3

Observation 300a8ff8-08ee-45fa-b3c4-a1ca464b12be · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 2022

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no resolver link, observed 2026-08-04T08:52:23.938212Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:23.938212Z digest=sha256:9a3985ac53f12909a1909713a40434073654b9a81b15a6f6e4689fc948f05e86

Observation de3cb4bd-b037-45a1-93c8-ceef14dd87e3 · outbound

This paper cites AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors

Reference 2023

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no resolver link, observed 2026-08-04T08:52:21.758006Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:21.758006Z digest=sha256:bf8942e084d928c5d81ffb5a660945aded2e17ad5c6bc837d8878f86b56a2037

Observation 9ba2c58f-db2f-48c2-8fcb-6994d5a26098 · outbound

This paper cites JMLR.org.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows JMLR.org

Reference 2024

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no resolver link, observed 2026-08-04T08:52:21.963495Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:21.963495Z digest=sha256:bde56f87ef32aefc4ebe72da1efcc22558ae1d09f88df22a7b946942699060f0

Observation 62a38b24-ba37-4287-ac10-73c49b47349a · outbound

This paper cites Automated Design of Agentic Systems.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows Automated Design of Agentic Systems

Reference 2025

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source=pdf_text observed=2026-08-04T08:52:22.238228Z digest=sha256:71293cba8cebd9991ec9384359abbf4e83a832b9cf766a74a9117191fbf433df

Observation 07575100-017f-476e-9808-013630192ddd · outbound

This paper cites EvoFlow: Evolving Diverse Agentic Workflows On The Fly.

Global Optimization and Inference-Time Region Grafting for Agentic Workflows EvoFlow: Evolving Diverse Agentic Workflows On The Fly

Reference 2026

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no resolver link, observed 2026-08-04T08:52:24.430006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:24.430006Z digest=sha256:5cd3dd1d543d2b5dc4d1f5b3fa4a4298e0cc5ee8913ef599c474e33c7f204bf8

Pith citing papers

No inbound Pith citation observations are available.