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Paper Citation Record · LEDGER

Global Optimization and Inference-Time Region Grafting for Agentic Workflows

As of 21 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 2026-08-21T06:32:19.484+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

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  • 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=sha256:1f209b649d390a5d4cd46f40795602c692e0ed847f4c75743b52a16059d0a056

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:21.880653Z digest=sha256:7dec88b5358a5abe78820ffc1bca5e5cfc357c304587da72876f975274947942

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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no resolver link, observed 2026-08-04T08:52:22.058758Z

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source=pdf_text observed=2026-08-04T08:52:22.058758Z digest=sha256:816a2b2c5f5200122ce66e0174d7bc3aa90fdffd52cf04b734e56846982fc54a

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=sha256:9f8fe032cbdefe1cc52e13a1b669ee03694978716fd9eced1184641edc0d8907

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:a8283b05e665e3373c6d626edb29afb3a97b07b9c41419ecb56dc6a0f1f0211c

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:22.773150Z digest=sha256:6c1b18b9422ea16d84f738688073e3fabceac8184399c6bcdacfc6fb63cca2ff

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:22.942819Z digest=sha256:1281a359cb8a346692eb98599d50409ad87351f72d546105022a1efa92f7a9d1

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:23.152337Z digest=sha256:a433b3b749886ab37f157192ed765fabfa9ba1e9e15a213c3527565a5337c5d6

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:23.399703Z digest=sha256:0257cb76e8973676a3599e57101cd51e61ff514394c4d08e4bd247844bb2d31c

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:a039c910cf475d2eef6e06c429e883c703e72f6a40ece73d0cadd206d48edb59

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:23.741422Z digest=sha256:e6696e168ff8f1db65a9ba1fae1817ffa0a2ddbb13e0dcc332bcba63820cbd07

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=sha256:44b1ee21bca7e9651f70e9e79460fd02f4d336c96555cbd1993e52b48b7088a2

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=sha256:245ce6d40b78aeacbc0fd68747c2414ee5bc925245988d7112c835c96d8622f0

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:22.391046Z digest=sha256:ca4ada503d2b206cf3a805e6b55f62fe41139c4c1989739478c3b38e8346e909

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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source=pdf_text observed=2026-08-04T08:52:21.501302Z digest=sha256:60436fe037f88cf786377696b9382f74e12ebd947f33aef1355a12edfa9f2bcf

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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no resolver link, observed 2026-08-04T08:52:21.436132Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:52:21.436132Z digest=sha256:746d317265c4577b66e1d1213b2f21490e1ff303bae1f239852db37413993241

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=sha256:96caf88f6e56f045c7ec43242a84295d641f513b86f8a17629895e3b7ce01ee1

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=sha256:74ed42d6e4c17947efdc0ac2bf421deccdd8258c6529da4d4a63b6747622220b

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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source=pdf_text observed=2026-08-04T08:52:21.963495Z digest=sha256:72d52b463f3b34b2dfca56f355ceeb78e68e786209f0e5bddb9e15e16489ebe4

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:cd8c6fae76046ddddb6e463eabfb52fd44952374280d5f23b67fc0f65fd99e8c

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=sha256:9779d62bdb5010d7459191f71cbe83238806e3336809dc76c276928ae1bb0cc6

Pith citing papers

No inbound Pith citation observations are available.