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Paper Citation Record · LEDGER

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems

As of 8 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2506.11803.

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

pith.paper-citation-record.v1
2506.11803 v2

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:10:42.528027Z

measured 41 of 41 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T11:20:50.996233Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

  • verified exact0
  • verified fuzzy29
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation afa6fafe-13dc-45fd-a331-aa3fa9740630 · outbound

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

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Generative agents: Interactive simulacra of human behavior,

Reference 1

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no resolver link, observed 2026-08-07T04:10:41.325236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:10:41.325236Z digest=sha256:09a44514095b128c53abda13f1c7d206a4e849e08c36c33f5db60a97c8564ec6

Observation ea6b15a1-d5eb-4bdb-bc6a-91a74d8f3756 · outbound

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

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 2

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no resolver link, observed 2026-08-07T04:10:41.330147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:10:41.330147Z digest=sha256:534c5b3117b39931de303d5d28c83314dee7ec34290cb80bf7e02e4516cdedd9

Observation 2467ec60-0d05-4919-a10a-4a2f7079d218 · outbound

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

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 3

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no resolver link, observed 2026-08-07T04:10:41.334878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:10:41.334878Z digest=sha256:33646f23badc8f64376758adada6843d4159cb8ab573f50b364db8f89b9ba81d

Observation 15846eae-8c9a-43ef-b68b-eb636dd63cb0 · outbound

This paper cites Coordinated multi-robot exploration,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Coordinated multi-robot exploration,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-07T04:10:49.669464Z

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=2026-08-07T04:10:41.339412Z digest=sha256:6bd4f95cb35b03c450baee276b093dcb2eb49451da694f1e70a8441cda20aa15

Observation 942c67fb-874e-4b68-9db7-39dd672cf269 · outbound

This paper cites Inner Monologue: Embodied Reasoning through Planning with Language Models.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Inner Monologue: Embodied Reasoning through Planning with Language Models

Reference 5

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no resolver link, observed 2026-08-07T04:10:41.344477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:10:41.344477Z digest=sha256:4857d889692de8606d62847aa5dc8a7f3d1272c2502d1e376313744f61704200

Observation 4a3b1749-6683-4ae2-a53f-1b7ae7a4f4cc · outbound

This paper cites Lamm: Language- assisted multi-modal instruction-tuning dataset, frame- work, and benchmark,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Lamm: Language- assisted multi-modal instruction-tuning dataset, frame- work, and benchmark,

Reference 6

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raw_fallback, observed 2026-08-07T04:10:49.312514Z

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=2026-08-07T04:10:41.349139Z digest=sha256:7e99bb5efeb50137b9a572aa4850818ae3f0b816c97cc6ffba56b7ea15f86967

Observation af48ac2b-c579-43b4-a091-bed3a5347640 · outbound

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

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face,

Reference 7

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raw_fallback, observed 2026-08-07T04:10:49.031370Z

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=2026-08-07T04:10:41.354023Z digest=sha256:d16ccab62d11e44392cfd41dacfb688284de0424dccdfb9d709192f97bb3072b

Observation 9c7e3929-d5c9-4e23-a1bf-b0f002dc940c · outbound

This paper cites LLM Multi-Agent Systems: Challenges and Open Problems.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems LLM Multi-Agent Systems: Challenges and Open Problems

Reference 8

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no resolver link, observed 2026-08-07T04:10:41.358929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:10:41.358929Z digest=sha256:2244d72560ef9ab355b554f8cb43f68a8377a25c08811b296141d14a56141ee1

Observation df940994-2353-4cbb-b298-2580ab026c95 · outbound

This paper cites Large language models empowered agent- based modeling and simulation: A survey and perspec- 10 tives,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Large language models empowered agent- based modeling and simulation: A survey and perspec- 10 tives,

Reference 9

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raw_fallback, observed 2026-08-07T04:10:48.816351Z

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=2026-08-07T04:10:41.363540Z digest=sha256:061e409c33d2439d020d75d76633a00963b26c54347817c844fdf7b1af59f224

Observation 7211b4c0-47c0-4d31-96e0-91825a1790cf · outbound

This paper cites Learning multiagent communication with backpropagation,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Learning multiagent communication with backpropagation,

Reference 10

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raw_fallback, observed 2026-08-07T04:10:48.606793Z

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=2026-08-07T04:10:41.367630Z digest=sha256:da8c5ab7d99a87f88b539b26af591057d623041ecb7a4d5b6d2b0f28a3d18999

Observation d1692a16-0373-47cb-9f4d-56167e52f125 · outbound

This paper cites Learning to communicate with deep multi-agent reinforcement learning,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Learning to communicate with deep multi-agent reinforcement learning,

Reference 11

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raw_fallback, observed 2026-08-07T04:10:48.406331Z

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=2026-08-07T04:10:41.371548Z digest=sha256:520e17dda3bb50e4cef9633c7fe19893356a6e41192da9af2e8fd210e46b1216

Observation 14384e2e-1055-4083-bd66-8c14a619f43a · outbound

This paper cites Tarmac: Targeted multi-agent communication,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Tarmac: Targeted multi-agent communication,

Reference 12

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raw_fallback, observed 2026-08-07T04:10:48.191741Z

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=2026-08-07T04:10:41.375733Z digest=sha256:a3a3a20176a5d6b19d746446ef36eb99bffded4e229607b028b2f0d036d0c301

Observation 9929b8e1-fb29-4cf5-ae54-ecd808bc2e23 · outbound

This paper cites Opv2v: An open benchmark dataset and fusion pipeline for perception with vehicle-to-vehicle communication,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Opv2v: An open benchmark dataset and fusion pipeline for perception with vehicle-to-vehicle communication,

Reference 13

Resolution
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raw_fallback, observed 2026-08-07T04:10:47.810199Z

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=2026-08-07T04:10:41.379908Z digest=sha256:997633b9b307ed12bfcfff020f957ff15147d86335908a5e01b66aec63f22367

Observation 71f28fd0-a99a-4bd1-b743-c6ee5f494998 · outbound

This paper cites Learning distilled collaboration graph for multi-agent perception,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Learning distilled collaboration graph for multi-agent perception,

Reference 14

Resolution
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raw_fallback, observed 2026-08-07T04:10:47.490513Z

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=2026-08-07T04:10:41.384290Z digest=sha256:edbe9d3569f1ad17175c9cd460f27f96f667baab7386c3e27ce9c3972a92329d

Observation 814ab070-fcc0-4aa1-bc9b-a6b686755b0e · outbound

This paper cites Mkd-cooper: cooperative 3d object detection for autonomous driving via multi-teacher knowledge distillation,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Mkd-cooper: cooperative 3d object detection for autonomous driving via multi-teacher knowledge distillation,

Reference 15

Resolution
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raw_fallback, observed 2026-08-07T04:10:47.140007Z

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=2026-08-07T04:10:41.391725Z digest=sha256:619ebeae021c165075099ca11c5a658c90c054360dbad0b784d9acaf1e3a26ef

Observation 3c1aa75f-3d44-49ea-9fae-acc82f7a238a · outbound

This paper cites Lora: Low-rank adaptation of large language models,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Lora: Low-rank adaptation of large language models,

Reference 16

Resolution
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raw_fallback, observed 2026-08-07T04:10:46.915552Z

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=2026-08-07T04:10:41.410980Z digest=sha256:64ebb59b8d31526f8882bf1da29b3f790fb5ec4d44e25641e2bc4227a5773628

Observation 50d03764-f571-4b2c-87e6-fd6d9761cef1 · outbound

This paper cites Parameter-efficient transfer learning for nlp,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Parameter-efficient transfer learning for nlp,

Reference 17

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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=2026-08-07T04:10:41.430493Z digest=sha256:9a9833c6fd632e3e1e540d0419f271ae1b550d1d985416693e192785b444f0ba

Observation 76da8937-7454-4cfb-b332-03ab94e8f3ae · outbound

This paper cites Emp: Edge-assisted multi-vehicle per- ception,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Emp: Edge-assisted multi-vehicle per- ception,

Reference 18

Resolution
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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=2026-08-07T04:10:41.448274Z digest=sha256:ec6d0e011d04dd5b6fd748a108a4489f7930487f153c1e1f81d3a9fd483ee960

Observation 821fcc1b-a4d8-4c71-8402-776bb77d7955 · outbound

This paper cites Edgecooper: Network-aware cooperative li- dar perception for enhanced vehicular awareness,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Edgecooper: Network-aware cooperative li- dar perception for enhanced vehicular awareness,

Reference 19

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raw_fallback, observed 2026-08-07T04:10:46.135000Z

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=2026-08-07T04:10:41.470994Z digest=sha256:26c42dde23d56a60b0930ef20ea74eea68003e1f7ea9ff3fb6ffd62dd4f860b9

Observation f959833d-b6fd-47d5-986e-57bb935805ff · outbound

This paper cites Cooperative perception and localization for cooperative driving,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Cooperative perception and localization for cooperative driving,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-07T04:10:45.945619Z

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=2026-08-07T04:10:41.487327Z digest=sha256:bf2b9d40de313495e23850a3f68a4c3190e6ea6cb4e664567b12a6fac986054f

Observation 0b6199f1-c9fd-4e90-ac27-d0dd981b4b9f · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 21

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no resolver link, observed 2026-08-07T04:10:41.496566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:10:41.496566Z digest=sha256:8d925773e9104bf7c0997f49fff0cc126c4a4021d548c304fba30901e05f59a4

Observation a8e34cc2-9bef-4822-a816-df614b025a2c · outbound

This paper cites The power of scale for parameter-efficient prompt tuning,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems The power of scale for parameter-efficient prompt tuning,

Reference 22

Resolution
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raw_fallback, observed 2026-08-07T04:10:45.691973Z

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=2026-08-07T04:10:41.510547Z digest=sha256:2672755851ed7987cf7bbf70c058d3f4c97fce28a50f49abee3c026c0ade6056

Observation 5ebc8891-871b-48af-96b6-5af6d91fe124 · outbound

This paper cites Learning to prompt for vision-language models,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Learning to prompt for vision-language models,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:10:45.518220Z

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=2026-08-07T04:10:41.522189Z digest=sha256:bc00191649035d722e7d1a6edc9f4553decad9d41b848b10796b452595ddf6f0

Observation e22cac47-19fd-48b7-8099-29401fa208da · outbound

This paper cites Visual prompt tuning,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Visual prompt tuning,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:10:45.347953Z

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=2026-08-07T04:10:41.532810Z digest=sha256:2c17fd15ae685abc6f9427a6af722c68d537c7b6fefc2203a9d2f3a3c0444e07

Observation f29d284f-e13e-4d3c-9b55-6abfcfcf8a41 · outbound

This paper cites Adaptive parameter-efficient fine-tuning for vision transformers,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Adaptive parameter-efficient fine-tuning for vision transformers,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:10:45.122569Z

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=2026-08-07T04:10:41.547854Z digest=sha256:bb04b8ed91f5deb473eacbcf59eb67ceb2b1b1ec2cd307770427a90dfb46766b

Observation 37c431fd-b76f-4943-9a2d-1c3417bc8fc0 · outbound

This paper cites Com- pacter: Efficient low-rank hypercomplex adapter layers,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Com- pacter: Efficient low-rank hypercomplex adapter layers,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:10:44.879756Z

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=2026-08-07T04:10:41.563887Z digest=sha256:aa4cfa39f2029916429a8d0d588a6b13f8ed21286fd08f19ba0afcc0bdc9923b

Observation 314c6576-7453-4729-8569-67bf233a73f0 · outbound

This paper cites an unresolved cited work.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-07T04:10:44.686102Z

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=2026-08-07T04:10:41.578077Z digest=sha256:d8cb64bc01bfe1edba41b58556685bd132006fa5a655e60d98556a5104ae9448

Observation 3ef1ff6a-7f7f-4f62-b88b-2b8554c70cf8 · outbound

This paper cites Deprl: Achieving linear convergence speedup in personalized decentralized learning with shared representations,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Deprl: Achieving linear convergence speedup in personalized decentralized learning with shared representations,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:10:44.499756Z

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=2026-08-07T04:10:41.597864Z digest=sha256:68046653f01e573913e5e8114e303114f21566a9c8006518fee39cce65b040ae

Observation 296b5f22-01bd-48b6-aeca-193bcf5513f6 · outbound

This paper cites Stochastic gradient push for distributed deep learn- ing,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Stochastic gradient push for distributed deep learn- ing,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:10:44.303060Z

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=2026-08-07T04:10:41.616070Z digest=sha256:3dbabd66b8378e3e83be20e7edb4dcc5be71b186c5efa320ee9fbfa77ec22f05

Observation 6fa5542b-2cb5-46b8-8353-425bfae625fe · outbound

This paper cites Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent,

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T04:10:41.694597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:10:41.694597Z digest=sha256:183ccb767ccef967a4e4e774dbebc6b48d3369fe5b833e222fca9509de5bcf3d

Observation 45b5ff0c-0c2b-436d-bc9f-675d8a0e9dab · outbound

This paper cites Deep hashing network for unsupervised do- main adaptation,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Deep hashing network for unsupervised do- main adaptation,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:10:44.120613Z

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=2026-08-07T04:10:41.833680Z digest=sha256:0c6970d50900e9125ccbf11724aeb83e81333cd2863ed933132799eb8658a9a0

Observation 2823c6b2-24e2-487c-bfb0-ce4334caebf8 · outbound

This paper cites Geodesic flow kernel for unsupervised domain adaptation,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Geodesic flow kernel for unsupervised domain adaptation,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:10:43.931694Z

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=2026-08-07T04:10:41.929448Z digest=sha256:5287a0d7984fd0189597273eedc6b0dc41a377f8c95fcfe52e4bd4d1f7724f4b

Observation 1ed91973-6cee-4921-9ec3-32b9575e3d13 · outbound

This paper cites Moment matching for multi-source domain adaptation,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Moment matching for multi-source domain adaptation,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:10:43.752848Z

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=2026-08-07T04:10:41.986855Z digest=sha256:ce49dc3d0c19cb7d67a5391325fa0d33039ef67e824767b0a7a3c55321eca365

Observation 2a03393d-bb1b-4561-b778-2e215b4f7517 · outbound

This paper cites Think Locally, Act Globally: Federated Learning with Local and Global Representations.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Think Locally, Act Globally: Federated Learning with Local and Global Representations

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T04:10:42.051401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:10:42.051401Z digest=sha256:ea0e88eac481647dea3b18bc0ea532a9593ede50bf0c9bada084833869f6b6ca

Observation 382375e6-2405-4e1d-ba07-1737ac3e815e · outbound

This paper cites Exploiting shared representations for personalized fed- erated learning,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Exploiting shared representations for personalized fed- erated learning,

Reference 35

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Observation 572bbead-60a3-4a6b-8cad-23a4f512e84b · outbound

This paper cites Automatic differentiation in pytorch,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Automatic differentiation in pytorch,

Reference 36

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Observation 26359246-0f9c-4fc3-873e-ea16207b9847 · outbound

This paper cites Optimization methods for large-scale machine learning,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Optimization methods for large-scale machine learning,

Reference 37

Resolution
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Observation a92c44f0-0ac9-42ea-807a-64ebf0885610 · outbound

This paper cites Adaptive Federated Optimization.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Adaptive Federated Optimization

Reference 38

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Observation f357125f-9210-4139-9e26-8bdb852dca42 · outbound

This paper cites Distributed Subgradient Methods for Multi-Agent Optimization,.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Distributed Subgradient Methods for Multi-Agent Optimization,

Reference 39

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Observation cfae9502-4693-49ab-8553-68094a1d7ec9 · outbound

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PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems Unresolved cited work

Reference 40

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Pith citing papers

Observation 892ce47d-c3f6-4369-a6c2-462e93dfa8a1 · inbound

In-the-Flow Agentic System Optimization for Effective Planning and Tool Use cites this paper.

In-the-Flow Agentic System Optimization for Effective Planning and Tool Use PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems

Reference 2025

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