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Paper Citation Record · LEDGER

Adaptive Multi-Agent Reasoning via Automated Workflow Generation

As of 10 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2507.14393.

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

pith.paper-citation-record.v1
2507.14393 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:10:33.039035Z

measured 35 of 35 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T08:17:10.481202Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T12:15:01.137692Z

Reference resolution

34 of 34 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1c48ae81-0063-4d53-b236-bec6b3fc623b · outbound

This paper cites The illusion of thinking: Understanding the strengths and limitations of reasoning models via the lens of problem complexity,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation The illusion of thinking: Understanding the strengths and limitations of reasoning models via the lens of problem complexity,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:37.572466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:27.902709Z digest=sha256:6bead30e6c60a16ed6c0a147262080b973c0414bdb3edc994fa71deb039156ac

Observation 43368a14-92ee-42fa-ae30-213a195fa693 · outbound

This paper cites What has a foundation model found? using inductive bias to probe for world models,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation What has a foundation model found? using inductive bias to probe for world models,

Reference 2

Resolution
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no resolver link, observed 2026-08-06T16:10:27.968218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:27.968218Z digest=sha256:906f255b50a731b5588b7656635754954e16cce15401b10064840ed2f8cc8a8a

Observation 5bd5e6eb-cc45-4c2c-86be-6c3bc8d50bba · outbound

This paper cites Faith and fate: Limits of transformers on compositionality,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Faith and fate: Limits of transformers on compositionality,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:37.415107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:28.041288Z digest=sha256:36f06204056cb2de5095f26d4ae4c55ee090fa1b995018510f6cbffa3fceeab4

Observation 857c4cbc-4b4f-453d-ae6e-adfb40d7a830 · outbound

This paper cites Unveiling causal reasoning in large language models: Reality or mirage?.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Unveiling causal reasoning in large language models: Reality or mirage?

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:37.160786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:28.113829Z digest=sha256:50eb862ebdc1a94e8a9fa3dc6db7f2b010389404c29d1550abc0020d06766b19

Observation a6ace9b7-614f-4344-a2af-50d24872b524 · outbound

This paper cites Large Language Models Are Not Strong Abstract Reasoners.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Large Language Models Are Not Strong Abstract Reasoners

Reference 5

Resolution
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no resolver link, observed 2026-08-06T16:10:28.200105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:28.200105Z digest=sha256:33fed4de4ff9a37ae18018b68dff342844980faafde60338dcb09218ba425a83

Observation df5a10f9-4434-46e4-9ae7-06f36e703b51 · outbound

This paper cites Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data

Reference 6

Resolution
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no resolver link, observed 2026-08-06T16:10:28.285063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:28.285063Z digest=sha256:a34c00680ef3ddeba424c34f947f6d881953dbfefbaa3a6512af7a679b3c92d7

Observation d773d001-007a-45e6-8ad1-31ac21e17281 · outbound

This paper cites On Memorization of Large Language Models in Logical Reasoning.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation On Memorization of Large Language Models in Logical Reasoning

Reference 7

Resolution
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no resolver link, observed 2026-08-06T16:10:28.371589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:28.371589Z digest=sha256:d773b421e67cc44a745bcdd711094c6411ed9dd971df5d52e4868e68ef5c22a5

Observation 034c6e2a-7d77-4496-a62f-096fb7d4a8b9 · outbound

This paper cites Recitation over reasoning: How cutting-edge language models can fail on elementary school-level reasoning problems?.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Recitation over reasoning: How cutting-edge language models can fail on elementary school-level reasoning problems?

Reference 8

Resolution
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no resolver link, observed 2026-08-06T16:10:28.462226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:28.462226Z digest=sha256:ee86b051725efd1441c3893281b1d6cdf4366da7d78eec393ab2323a38a8cfbd

Observation 873dafec-47b0-48d3-ad80-bc0384e30327 · outbound

This paper cites Reasoning or reciting? exploring the capabilities and limitations of language models through counterfactual tasks,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Reasoning or reciting? exploring the capabilities and limitations of language models through counterfactual tasks,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:36.931861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:28.546277Z digest=sha256:a2b9867c2bd0d138f6e8af3acbbccdd23e2c54b9715dd68d932e77e02f85ea46

Observation ca396ef6-9d3c-4f2b-bd7c-4cc78d7acaac · outbound

This paper cites What Do Learning Dynamics Reveal About Generalization in LLM Reasoning?.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation What Do Learning Dynamics Reveal About Generalization in LLM Reasoning?

Reference 10

Resolution
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no resolver link, observed 2026-08-06T16:10:28.644012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:28.644012Z digest=sha256:7d67d8d24c3ca528da622f742c9ee9c8c989b17c5ca393bdea87db8e08bdfc41

Observation 3de1f704-e147-4c3d-8796-5e9311ed5557 · outbound

This paper cites The Reasoning-Memorization Interplay in Language Models Is Mediated by a Single Direction.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation The Reasoning-Memorization Interplay in Language Models Is Mediated by a Single Direction

Reference 11

Resolution
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no resolver link, observed 2026-08-06T16:10:28.716786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:28.716786Z digest=sha256:04393cd02b811ba09ee220eba5d25d469d75467b78534aac7027aec4aa8257c0

Observation b1fed61d-ff21-45e2-924a-1ab006bd0417 · outbound

This paper cites Nexus: A Lightweight and Scalable Multi-Agent Framework for Complex Tasks Automation.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Nexus: A Lightweight and Scalable Multi-Agent Framework for Complex Tasks Automation

Reference 12

Resolution
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no resolver link, observed 2026-08-06T16:10:28.786956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:28.786956Z digest=sha256:ef32ead73a81a5d6944c6ee71c900420fcdfd78881418adb3c8679992f8a5f61

Observation 2095314a-c710-4b48-af42-e2252054df52 · outbound

This paper cites Intelligent agents: Theory and practice,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Intelligent agents: Theory and practice,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T16:10:28.857745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:28.857745Z digest=sha256:7868eeaf19fcdd567f366b566199000f84384568e3ae3d8a18f10b67cf8322af

Observation 3923469e-6449-48ed-985f-394fb2430f49 · outbound

This paper cites Multiagent systems: A survey from a machine learning perspective,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Multiagent systems: A survey from a machine learning perspective,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:36.817176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:28.940381Z digest=sha256:a3af728fb60c5ea54de9f43deab69d1b57ec5302329d638f7fdbe50d271d82aa

Observation a313a54e-9393-4069-8d62-9b539c001d00 · outbound

This paper cites Generative agents: Interactive simulacra of human behavior,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Generative agents: Interactive simulacra of human behavior,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:36.656788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:29.045669Z digest=sha256:8a45f995291605ba37b67431669a8c19ead4499fc3da7b3a75ef9c0867a5b076

Observation d561dc61-a6b9-4d6e-858a-1bf5ba5c767b · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation ReAct: Synergizing Reasoning and Acting in Language Models

Reference 16

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no resolver link, observed 2026-08-06T16:10:29.159833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:29.159833Z digest=sha256:cc2b0701f3d2588493d6fe7cf61a378b3bdf715fce2cbafd1d7327fbfbb2ea11

Observation 0b084407-014b-4cb2-b5e2-f7fbb3bc8cff · outbound

This paper cites (2025) AutoGPT: Build, Deploy, and Run AI Agents.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation (2025) AutoGPT: Build, Deploy, and Run AI Agents

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:36.472245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:29.239596Z digest=sha256:25ca6eaf823ac0c3a6a7d3900060fcb701c8f84583de9a38132d5afa3a8d4d7b

Observation 4ba3a371-f4ab-4dcf-b7bd-85760557c500 · outbound

This paper cites Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:36.276966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:29.335961Z digest=sha256:7f64b659380cc38f2b3684952a2ca5e5ac188a682c776f166fc8e2a4e12df688

Observation 44a37974-ff21-4c3d-84a8-3c75b7325f29 · outbound

This paper cites (2025) LangGraph.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation (2025) LangGraph

Reference 19

Resolution
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raw_fallback, observed 2026-08-06T16:10:36.042690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:29.415787Z digest=sha256:19dd993a3c6a65b00ca3675971a4939c596334546dcb958774964fc1d5ea4e3f

Observation b74e5b65-f3b5-4a24-973c-62062ffd24f3 · outbound

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

Adaptive Multi-Agent Reasoning via Automated Workflow Generation AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 20

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no resolver link, observed 2026-08-06T16:10:29.497025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:29.497025Z digest=sha256:4f374743c2709a01cd5013f38d5e22a911828b912dfcdfcaa3ee135bbfce9361

Observation 0378461b-435f-4c43-8bc0-38e7c76abaac · outbound

This paper cites (2025) CrewAI: Production-grade framework for orchestrating sophisticated AI agent systems.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation (2025) CrewAI: Production-grade framework for orchestrating sophisticated AI agent systems

Reference 21

Resolution
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raw_fallback, observed 2026-08-06T16:10:35.828699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:29.518703Z digest=sha256:8ced724feacc91a33740e6aa81b0e30d380476a21ddc41738cdd2a47f03cec15

Observation c04511ac-165b-4a6c-bba1-5e10ad3fa36c · outbound

This paper cites Model Context Protocol (MCP),.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Model Context Protocol (MCP),

Reference 22

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raw_fallback, observed 2026-08-06T16:10:35.628764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:29.579531Z digest=sha256:83f86b55fd4abd1524fdb65d974c22a3fa6afa13ab27db5eca25ce3dd93c3b2c

Observation 40252eba-95af-468e-a2c8-79350f382ea1 · outbound

This paper cites PRewrite: Prompt Rewriting with Reinforcement Learning.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation PRewrite: Prompt Rewriting with Reinforcement Learning

Reference 23

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no resolver link, observed 2026-08-06T16:10:29.678221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:29.678221Z digest=sha256:898ee8a07d6cb4d267a7b4484fc04ca2accc5904bd5bf8a7486e79f133054ddf

Observation 10721a0b-ce1b-41e7-9868-1a2faca34f05 · outbound

This paper cites System prompt optimization with meta-learning,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation System prompt optimization with meta-learning,

Reference 24

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no resolver link, observed 2026-08-06T16:10:29.787447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:29.787447Z digest=sha256:977948a945d86ca2ce094679b3ecc12e7d6f4b4a6534a59711e385d91dcdf9e4

Observation 9bc88578-a089-422e-9323-04e0bf8a3463 · outbound

This paper cites Llama 4 scout and maverick: Mixture-of-experts multimodal models,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Llama 4 scout and maverick: Mixture-of-experts multimodal models,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:35.426925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:29.874036Z digest=sha256:c8199106254133f8938c5ce002c9c92b051aeda90301e1c93906500e4835311a

Observation afa13c3a-43ca-4d50-9d64-67fed195df6d · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 26

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no resolver link, observed 2026-08-06T16:10:30.095085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:30.095085Z digest=sha256:57ad23caadee969a8f6e1677a95359a9fd92b778a8d1c5beb7f7c4241585ab00

Observation 505cc5e2-55e8-4ef6-b469-019aa3a1eb40 · outbound

This paper cites Claude 3.5 Sonnet,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Claude 3.5 Sonnet,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:35.274881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:30.334142Z digest=sha256:81d1f83004d09720be32db794de1cb695159e441b95139ef6b91ab8f3a936331

Observation 1d8b2b96-03db-478b-bdcd-b6b0a860e5fe · outbound

This paper cites Introducing Claude 4,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Introducing Claude 4,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:35.089659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:30.540405Z digest=sha256:2ccb8b63ec1109be546ca85e90db3383bb61b8c54dbc548cda576c95c78d3d21

Observation 295663ef-755b-4f89-8704-dae46dab8b07 · outbound

This paper cites Gemini 2.5 flash preview – model card,.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Gemini 2.5 flash preview – model card,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:34.927390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:30.791423Z digest=sha256:361282e6ccf311fce22789f62dcc1d08689db4ac8081a31b97425a034b43f277

Observation 05100412-ac9e-4113-8b1c-0f78b10692ff · outbound

This paper cites an unresolved cited work.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:10:34.688381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:30.987590Z digest=sha256:580a037609118ea13c1acfab1e1619703871445a1ce486022d2c4e6cd3729b27

Observation 2eddf15b-d30a-4f2e-82d0-9d94e34938af · outbound

This paper cites an unresolved cited work.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:10:34.176274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:31.197894Z digest=sha256:390ec48510f615110855e301faf59352dfd147423a5933a2f34b01d6b9edef69

Observation a588812e-654b-44d1-81d0-88788446753c · outbound

This paper cites This feedback identifies issues, root causes, and required changes, and is sent to the Prompt Engineering stage.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation This feedback identifies issues, root causes, and required changes, and is sent to the Prompt Engineering stage

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:33.989694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:31.729845Z digest=sha256:560c02278714480a80f0c046c4c13beca9716097f7d6964c487c30878bf6ac38

Observation 7152ab16-8ccf-430e-b9f8-689b0bfdfeae · outbound

This paper cites an unresolved cited work.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation Unresolved cited work

Reference 33

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:10:33.801120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:32.893454Z digest=sha256:4ccb60ea303bb9b41f08f9d8b2d55bd9aa9eec1dc8c573eba1ea18e065aff67b

Observation fd4b4ca9-b54d-4b75-97fa-d8d52dda19ed · outbound

This paper cites meta" answer that prevents classic/technical solution. In several cases, Supervisor did not explicitly require agents to surface.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation meta" answer that prevents classic/technical solution. In several cases, Supervisor did not explicitly require agents to surface

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:10:33.593982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:10:33.039035Z digest=sha256:af42790f88d5b98acb0a040543f7e1410d84df2c6776530358c33a07adc84412

Pith citing papers

Observation dc2f46b0-756c-41ca-9528-324061b9b116 · inbound

Prompt Governance? On Governing Technologies Governed by Natural Language cites this paper.

Prompt Governance? On Governing Technologies Governed by Natural Language Adaptive Multi-Agent Reasoning via Automated Workflow Generation

Reference 297

Resolution
verified exact
arxiv_id, observed 2026-07-01T08:25:32.411323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-01T08:17:10.481202Z digest=sha256:f269b8b07e64c133328bec2c4d29f3ff7b326368bc1609bfa927941bd36885bc