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Paper Citation Record · LEDGER

Adaptive Graph Pruning for Multi-Agent Communication

As of 8 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 9 inbound Pith citation observations for arXiv:2506.02951.

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

pith.paper-citation-record.v1
2506.02951 v3

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:18:47.167943Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:18:44.092100Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T16:53:40.450246Z

Reference resolution

48 of 48 outbound references displayed

  • verified exact2
  • verified fuzzy5
  • unresolved41
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b910c5b0-c24d-456f-b73b-857eda7290eb · outbound

This paper cites Besta, N.

Adaptive Graph Pruning for Multi-Agent Communication Besta, N

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:18:51.951081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:41.581207Z digest=sha256:273ba48a620df6c6c1a9985ad7a498d2b8a42fe927755350ec1b882af6a5ce3f

Observation bb03c2cf-55e8-46ef-9339-dc5fda5a0b49 · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:18:51.692648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:41.678127Z digest=sha256:e351fb9a43afaacd76e564c7f10142c70b40f03d0abbc7bceafec7e0b6e28ee7

Observation fd5e7ea6-9862-429a-9ca7-593eac9d8350 · outbound

This paper cites AutoAgents: A Framework for Automatic Agent Generation.

Adaptive Graph Pruning for Multi-Agent Communication AutoAgents: A Framework for Automatic Agent Generation

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:41.831841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:41.831841Z digest=sha256:a6682058ee146a906bf626ac81e04ee4f429e59c4f7937ed80a6bd90834a1546

Observation 69c753b1-c500-4ef7-af71-757cf2840bd9 · outbound

This paper cites Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference Systems.

Adaptive Graph Pruning for Multi-Agent Communication Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference Systems

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:41.961925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:41.961925Z digest=sha256:ecf1e10b855583baf81d025b352512268a179ff932d901323e98502f41b7bc41

Observation 8374d701-288a-468a-aab0-89b632dfe15b · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:18:51.463156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:42.039257Z digest=sha256:b1a1769895f9b836e106f76c54ab25eda42ddc89761219958bf0c2228b189b93

Observation 0f979198-a4b0-4301-8a0b-208d47a6eea0 · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:18:51.193761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:42.158607Z digest=sha256:b77d362171dcff47abba1c9aae46c8873b1d05516b7b49008261c1ab30d0ce2d

Observation 306fc23c-d317-4f01-9c9f-223a1fd69ae2 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Adaptive Graph Pruning for Multi-Agent Communication Training Verifiers to Solve Math Word Problems

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:42.242385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:42.242385Z digest=sha256:3d0a54974e271a9370545c5707e9d23dc6a6a6843fe3514ee9917ffd22cd4118

Observation b59d94cf-cc0a-4499-8389-11e029cd64ce · outbound

This paper cites Improving Factuality and Reasoning in Language Models through Multiagent Debate.

Adaptive Graph Pruning for Multi-Agent Communication Improving Factuality and Reasoning in Language Models through Multiagent Debate

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:42.328390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:42.328390Z digest=sha256:1c147527f94e91651c1a3aafb0458fb9c411e161670d1144e9603ce00e9548dc

Observation cd00f561-4d8e-457f-9215-853c40887cc0 · outbound

This paper cites Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution.

Adaptive Graph Pruning for Multi-Agent Communication Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:42.454284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:42.454284Z digest=sha256:0837cd626cbc6256276e38507f1e857ceb7339880ceb7a09bf9455731c0ccd2d

Observation 78537f89-b0c2-4138-880a-28ec7b74c718 · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:18:50.934827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:42.542298Z digest=sha256:7d5818b16390bb67f2e24a6bd8bf3a0c8f01e85cd48adca00a9f3599bd4e1ac7

Observation 74857af2-446f-45f3-9db3-0459f5f9d124 · outbound

This paper cites EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers.

Adaptive Graph Pruning for Multi-Agent Communication EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:42.691961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:42.691961Z digest=sha256:c6819f471f288553ea7f292af215ea7628f103fc340bd5a57056dc393e3e303f

Observation fe0dd39a-2e43-4388-beea-ca721633d85d · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:18:50.588137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:42.803194Z digest=sha256:c7401fad890d594e130d305225de40cfd3ad74aee17ec71ccda9282de5b9ee18

Observation 2f220f76-21eb-4f6a-96aa-609b813e3556 · outbound

This paper cites Hendrycks, C.

Adaptive Graph Pruning for Multi-Agent Communication Hendrycks, C

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:18:50.294470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:42.930950Z digest=sha256:504055d43ce31ff39662aa1f5373c834ec8209840753b9e1a977edf69d36d0a4

Observation d4721ca8-983d-41e9-83f5-09a62f86970d · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:18:49.946286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:43.049727Z digest=sha256:064dff8d6883c336c43f5a7af9575ee795599486e13b6a383adbe55f65340f98

Observation 8c7d2e6c-f451-486f-bde7-ce85ad893467 · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:18:49.693114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:43.178951Z digest=sha256:8a9be170c2d14703b2fbacfb241e3c5c78baf43c397cb7fa00debed98eb29b82

Observation cb7e038c-4d99-4bb2-8c0e-da217acc0a9d · outbound

This paper cites Automated Design of Agentic Systems.

Adaptive Graph Pruning for Multi-Agent Communication Automated Design of Agentic Systems

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:43.304670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:43.304670Z digest=sha256:58073d45880c7a99d8fb08d5bdfc46eb5c03cd2efba8bda0f07f0b60e8410c59

Observation 70abaccb-c082-45ea-ae31-19ff9d009933 · outbound

This paper cites Learning Multi-Agent Communication from Graph Modeling Perspective.

Adaptive Graph Pruning for Multi-Agent Communication Learning Multi-Agent Communication from Graph Modeling Perspective

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:43.452061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:43.452061Z digest=sha256:d6634ce3b6f0a4423996bc0008cfa5c771eea7f5596ace18dd826e4d9aa876e7

Observation cd72863c-981f-48de-8f3f-a5690c06ab95 · outbound

This paper cites Self-Evolving Multi-Agent Collaboration Networks for Software Development.

Adaptive Graph Pruning for Multi-Agent Communication Self-Evolving Multi-Agent Collaboration Networks for Software Development

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:43.572297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:43.572297Z digest=sha256:36ee7bde1d8f6e339d29e86c3da9375a8469b173577f825d8e65ba17f5e772cb

Observation a34de830-fbe5-49ec-afda-4db6ebec76db · outbound

This paper cites Self-Organized Agents: A LLM Multi-Agent Framework toward Ultra Large-Scale Code Generation and Optimization.

Adaptive Graph Pruning for Multi-Agent Communication Self-Organized Agents: A LLM Multi-Agent Framework toward Ultra Large-Scale Code Generation and Optimization

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:43.770907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:43.770907Z digest=sha256:93142d56b6f5fcb1de4605102cb9745bc225e9d52ead9d4167c27bf25891527c

Observation 44cf69bb-105e-4c31-b619-7a31182896f0 · outbound

This paper cites Jiang, X.

Adaptive Graph Pruning for Multi-Agent Communication Jiang, X

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:18:49.503751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:43.885208Z digest=sha256:5da21cba2049c9d51b986760e8be10b181721269de82f69c826dabb3f93ea5a6

Observation c9a49cda-2e96-45a5-a8a3-666af904a5f4 · outbound

This paper cites DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines.

Adaptive Graph Pruning for Multi-Agent Communication DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:43.992573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:43.992573Z digest=sha256:acf2739408f6286cf95fca84d80e5738ee8ab2b160314ad2e709e9068f12f0bf

Observation de4a6875-e07e-4568-bf0a-176b9b285b0e · outbound

This paper cites Adaptive Graph Pruning for Multi-Agent Communication.

Adaptive Graph Pruning for Multi-Agent Communication Adaptive Graph Pruning for Multi-Agent Communication

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:44.092100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:44.092100Z digest=sha256:9e1a42a5918da1a5264f17d673fcb33b5fea4e6f5feb58e61f3c644904c66e00

Observation b4dea7c3-2c84-484e-9495-a5316eb8bbd1 · outbound

This paper cites Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems.

Adaptive Graph Pruning for Multi-Agent Communication Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:44.207275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:44.207275Z digest=sha256:fca92683ab5da0fcf3f80f16dcc87359301aafd55fe238248f2053a73877484b

Observation 48228321-ff7a-4e47-8d4b-2e45e389ee2c · outbound

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

Adaptive Graph Pruning for Multi-Agent Communication A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:44.316529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:44.316529Z digest=sha256:473093572f1e0f56b1a5227a8709b824760111648557f886e07a180d248b5797

Observation 0214f49e-f20f-4945-80c2-202344f26fe1 · outbound

This paper cites Are NLP Models really able to Solve Simple Math Word Problems?.

Adaptive Graph Pruning for Multi-Agent Communication Are NLP Models really able to Solve Simple Math Word Problems?

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:44.448300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:44.448300Z digest=sha256:76e508ec9ee1f66f3d1460a992a352a8ad5150ac577b200fbd5ea099a4d38c84

Observation d0e7f5d8-aa47-40f6-8af2-3be45af61185 · outbound

This paper cites Pesce and G.

Adaptive Graph Pruning for Multi-Agent Communication Pesce and G

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:18:49.294700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:44.539020Z digest=sha256:fb9399d5c2f278862047a2acf23b2df158dc161745997b157a7d9ca1ee111001

Observation 94fa6a01-c446-4867-ac8d-fca4eae062db · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:18:49.083165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:44.689794Z digest=sha256:81d0f15832129d982c102c44fc3d3b6830b9eb51d7de57657eab015e5b1cc1a0

Observation 46d18bc3-19de-430f-8fe0-6b452a4a6a73 · outbound

This paper cites Scaling Large Language Model-based Multi-Agent Collaboration.

Adaptive Graph Pruning for Multi-Agent Communication Scaling Large Language Model-based Multi-Agent Collaboration

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:44.814064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:44.814064Z digest=sha256:074edee9b64d14eeb1600c2860eca05ab66db45d87040c61f1a57394cdca26c5

Observation 57255405-a7e0-4657-a60f-333491071254 · outbound

This paper cites Solving General Arithmetic Word Problems.

Adaptive Graph Pruning for Multi-Agent Communication Solving General Arithmetic Word Problems

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:44.940664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:44.940664Z digest=sha256:f4207cbbf00140327dc2559788e52c2952d22ee0626dcbf357e29d43ac5bc1bb

Observation d0b0fc20-4df0-4637-bf25-66e469b44c6b · outbound

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

Adaptive Graph Pruning for Multi-Agent Communication AgentSquare: Automatic LLM Agent Search in Modular Design Space

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:45.056024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:45.056024Z digest=sha256:07de0f7b244a492c785199c9a0f6dd64284ed6d77c0ef195eba73d59b9cb0904

Observation f1cd3a05-4eba-40c7-9e9f-d36ab10c8c49 · outbound

This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

Adaptive Graph Pruning for Multi-Agent Communication Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:45.175031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:45.175031Z digest=sha256:ea11eb939afa738b59c1c00369b9c9bd6e4f8fd51f728e582dbe090b7bc8b54a

Observation 22c2abe9-8bef-48bb-86ba-785636b9b620 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Adaptive Graph Pruning for Multi-Agent Communication Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:45.265366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:45.265366Z digest=sha256:2fd3bb90c59dd4576491fdf0dc65805bf08a60416e78ac37fd4ba94893f2fb6e

Observation 3227e5ce-6ea1-408a-b4b8-d727f169efe0 · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:45.385655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:45.385655Z digest=sha256:26bb53611fb99a64a72c14e7f2bd7cd357ed6958c67131b8213f0d7c3e60882b

Observation e40db222-8ec6-4cf9-8f5b-dfbb4bc55ff2 · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:18:48.779426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:45.546480Z digest=sha256:0297b9f0ef55effda0aeb39a2de5ebf49a51fc4a3bc5c85b85b5cbb0ffcd6fde

Observation 8d51f70e-75fc-4882-b43e-9839eaf3e8be · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:18:48.507409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:45.646493Z digest=sha256:51d6ff053e633f6c0e37f52d3d095db40381cd2f7a85a0c86fd57473ad9edf6d

Observation eb7000f5-a9fb-472a-8c52-7ecf6bcc0886 · outbound

This paper cites an unresolved cited work.

Adaptive Graph Pruning for Multi-Agent Communication Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:18:48.276202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:45.791027Z digest=sha256:2d552ad5de2fcda47fb39fbaa134c701b01342499ddfa5a5c6df41394f5c20f7

Observation 6f58b387-8234-4874-99d8-9f0d56a139a1 · outbound

This paper cites EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms.

Adaptive Graph Pruning for Multi-Agent Communication EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:45.889608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:45.889608Z digest=sha256:f61797e2f82d173c90b27acbd583a62f39bffc8b8783b6797fa7ee6cc1a031fc

Observation d1a0072a-f301-47d9-8a5c-7e868a7e5a8c · outbound

This paper cites Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems.

Adaptive Graph Pruning for Multi-Agent Communication Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:45.986822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:45.986822Z digest=sha256:40acacdd3150ce434e0c980f5de7ba821e994ee1b97bda550e5fa59c05d7803f

Observation cec72ef1-53a1-4642-bbf9-4f79bc6d90af · outbound

This paper cites G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks.

Adaptive Graph Pruning for Multi-Agent Communication G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks

Reference 39

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source=pdf_text observed=2026-08-07T11:18:46.099826Z digest=sha256:7f039fe990339ec03672fa4ef8e71819f8617d34aee06abcf4eab705b633551c

Observation f5d90bcd-d383-4fd0-91eb-d7235b062fbb · outbound

This paper cites Multi-agent Architecture Search via Agentic Supernet.

Adaptive Graph Pruning for Multi-Agent Communication Multi-agent Architecture Search via Agentic Supernet

Reference 40

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source=pdf_text observed=2026-08-07T11:18:46.237941Z digest=sha256:9c3fd4f8f8660915b62649c0def0fac609a583b5377577f61d438590289f0057

Observation afcf7821-5f0e-457c-8df1-38c28bcd8f94 · outbound

This paper cites Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View.

Adaptive Graph Pruning for Multi-Agent Communication Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View

Reference 41

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source=pdf_text observed=2026-08-07T11:18:46.316475Z digest=sha256:823b8c6770f9fbf1733932e272f8fea8e5d6a4d9616d574887db7c2d573a85b8

Observation a72c9508-8c14-48f2-b680-91f1e825da70 · outbound

This paper cites AFlow: Automating Agentic Workflow Generation.

Adaptive Graph Pruning for Multi-Agent Communication AFlow: Automating Agentic Workflow Generation

Reference 42

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no resolver link, observed 2026-08-07T11:18:46.411855Z

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source=pdf_text observed=2026-08-07T11:18:46.411855Z digest=sha256:2448f4a76c40bdd41d5130d07377fbda8c4abcf497c0d9707676a8bc4f512c2e

Observation 77e60fa6-8c68-487c-8bd4-268cfe4ccbf3 · outbound

This paper cites See and Think: Embodied Agent in Virtual Environment.

Adaptive Graph Pruning for Multi-Agent Communication See and Think: Embodied Agent in Virtual Environment

Reference 43

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source=pdf_text observed=2026-08-07T11:18:46.557963Z digest=sha256:b8cc6d79748f012880a03038af883f2f87be5cecc8f483b75808dbf8609cbb3c

Observation 4cf03887-3e5d-4cbf-97e8-3b1abcf7464b · outbound

This paper cites Hierarchical Auto-Organizing System for Open-Ended Multi-Agent Navigation.

Adaptive Graph Pruning for Multi-Agent Communication Hierarchical Auto-Organizing System for Open-Ended Multi-Agent Navigation

Reference 44

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source=pdf_text observed=2026-08-07T11:18:46.670093Z digest=sha256:cb1a679c9fbdd5d3889221817b4056e033119d9c0da6316130ea3480ce85b0e7

Observation d0199a30-23c2-46a6-9a01-5fac88f204dc · outbound

This paper cites Do We Really Need a Complex Agent System? Distill Embodied Agent into a Single Model.

Adaptive Graph Pruning for Multi-Agent Communication Do We Really Need a Complex Agent System? Distill Embodied Agent into a Single Model

Reference 45

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verified exact
local_arxiv, observed 2026-08-07T11:18:47.742570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:46.772625Z digest=sha256:7be5ee57617d68f18e30bccbe1298dcc8fe7135bca0397d174f3c13d0d1bf3b3

Observation 0e418fa5-aaa0-4581-ab72-097aa2a8f0c1 · outbound

This paper cites RIG: Synergizing Reasoning and Imagination in End-to-End Generalist Policy.

Adaptive Graph Pruning for Multi-Agent Communication RIG: Synergizing Reasoning and Imagination in End-to-End Generalist Policy

Reference 46

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verified exact
local_arxiv, observed 2026-08-07T11:18:47.471736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:46.862570Z digest=sha256:71a887c7914f370775b2da466b54b7134e793b57db4ce1a115654d78e50ba4b1

Observation 8d5c5761-013b-439b-8053-a89b1157fb5b · outbound

This paper cites Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents.

Adaptive Graph Pruning for Multi-Agent Communication Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents

Reference 47

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source=pdf_text observed=2026-08-07T11:18:46.991142Z digest=sha256:8989b5a6976803022d44785f1569264380feacd5b532c4e2d503846840a5d15a

Observation 65225da3-726f-4913-b06e-a5bba3a8673f · outbound

This paper cites Dialogue History.

Adaptive Graph Pruning for Multi-Agent Communication Dialogue History

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-07T11:18:48.084252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:18:47.167943Z digest=sha256:bedadf134027cf6e76be35861a5a0eee993fcb89f250961b57bf71ef00bebb8c

Pith citing papers

Observation de4a6875-e07e-4568-bf0a-176b9b285b0e · inbound

Adaptive Graph Pruning for Multi-Agent Communication cites this paper.

Adaptive Graph Pruning for Multi-Agent Communication Adaptive Graph Pruning for Multi-Agent Communication

Reference 22

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source=pdf_text observed=2026-08-07T11:18:44.092100Z digest=sha256:9e1a42a5918da1a5264f17d673fcb33b5fea4e6f5feb58e61f3c644904c66e00

Observation 863fa5aa-b4ef-40a2-ae4e-30b33698bb4e · inbound

Graphs Meet AI Agents: Taxonomy, Progress, and Future Opportunities cites this paper.

Graphs Meet AI Agents: Taxonomy, Progress, and Future Opportunities Adaptive Graph Pruning for Multi-Agent Communication

Reference 114

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T23:26:51.542914Z digest=sha256:b7fe981c2a76c919bd64de8a8c7db15edc3de432ba1b86fd28775bf4687713e5

Observation 526522db-9735-4eed-a688-8b2bbd388c92 · inbound

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory cites this paper.

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory Adaptive Graph Pruning for Multi-Agent Communication

Reference 58

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metadata mismatch
arxiv_id, observed 2026-05-14T23:13:16.179140Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-14T23:13:15.016486Z digest=sha256:9d2165d1f60ef01103edd2edef183edeaf4625cbd98a5373cfd8944f8f9b7988

Observation e7913be0-9f9d-43af-8e33-fcacd6f197f0 · inbound

Conjunctive Prompt Attacks in Multi-Agent LLM Systems cites this paper.

Conjunctive Prompt Attacks in Multi-Agent LLM Systems Adaptive Graph Pruning for Multi-Agent Communication

Reference 17

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arxiv_id, observed 2026-05-10T08:17:37.671876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T08:13:42.401992Z digest=sha256:f491cc3848ee2d87a994f732196d12091d26678a1fade7b6cb6f5c10c69a4140

Observation 709dcbc3-94f2-4d6b-91b4-52dbbd826ede · inbound

MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer cites this paper.

MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer Adaptive Graph Pruning for Multi-Agent Communication

Reference 21

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verified exact
arxiv_id, observed 2026-05-20T14:38:21.586795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T14:35:46.376752Z digest=sha256:50a2f92ac063cb31e5747c577be67618b331646e1feaea78dd6b9d7be3fe74be

Observation 91cc8139-0728-4336-be24-57f274e9d28c · inbound

MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer cites this paper.

MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer Adaptive Graph Pruning for Multi-Agent Communication

Reference 21

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source=pdf_text observed=2026-07-12T16:38:30.296706Z digest=sha256:bec1f92d54b0b9f32648ece17fc49dc8b68f5c715ff1c1596bb7023eff47e6ca

Observation f3dc26ea-d1d2-4c07-ba62-33ac6ab99b35 · inbound

FALAT: Tracing Failures in LLM Agent Trajectories via Dependency-Guided Search cites this paper.

FALAT: Tracing Failures in LLM Agent Trajectories via Dependency-Guided Search Adaptive Graph Pruning for Multi-Agent Communication

Reference 40

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arxiv_id, observed 2026-06-28T18:42:29.562005Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-28T18:38:56.787942Z digest=sha256:ad38df0a9f582a6eaa95b2f38afe456096ad7ec56dab3fe2400562ecb265e7c3

Observation 5b51ec09-b23c-41a9-ad7b-2026b62ac983 · inbound

PEAR: Permutation-Equivariant Adaptive Routing Multi-Agent Debate cites this paper.

PEAR: Permutation-Equivariant Adaptive Routing Multi-Agent Debate Adaptive Graph Pruning for Multi-Agent Communication

Reference 20

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metadata mismatch
arxiv_id, observed 2026-06-29T16:53:40.451745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-29T16:52:38.323900Z digest=sha256:2155ad157a19d69494a3f722cb338c96349ca01305c2fd9083e4fea994874def

Observation 90cb6b53-d4fa-4a94-97b5-d55bc11162ef · inbound

From Cognitive Architectures to Language Agents: A Mechanism-Level Review of Lineage, Convergence, and Migration Gaps cites this paper.

From Cognitive Architectures to Language Agents: A Mechanism-Level Review of Lineage, Convergence, and Migration Gaps Adaptive Graph Pruning for Multi-Agent Communication

Reference 46

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:30:37.739208Z digest=sha256:3ae140b3dae0aa17b3c52d218a5d2fd38900b0bd9682a3835e0fafddda0e9db2