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Paper Citation Record · LEDGER

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning

As of 21 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2608.07730.

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

pith.paper-citation-record.v1
2608.07730 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:27:13.378355Z

measured 53 of 53 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

53 of 53 outbound references displayed

  • verified exact2
  • verified fuzzy30
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d797dab2-0953-40da-b082-0fd76d6159a4 · outbound

This paper cites Communication-Efficient Learning of Deep Networks from Decentralized Data,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Communication-Efficient Learning of Deep Networks from Decentralized Data,

Reference 1

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 4d79b856-f77f-449c-a34e-90937e79776a · outbound

This paper cites Advances and Open Problems in Federated Learning,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Advances and Open Problems in Federated Learning,

Reference 2

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.199269Z digest=sha256:cd361554d42b36cd6b2075f20c050425709c0c93a8b0e37852404b7e58bacc25

Observation c90fd4e3-4b7b-42ef-84b6-4a76f8147b7a · outbound

This paper cites Combining Fed- erated Learning and Edge Computing Toward Ubiquitous Intelligence in 6G Network: Challenges, Recent Advances, and Future Directions,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Combining Fed- erated Learning and Edge Computing Toward Ubiquitous Intelligence in 6G Network: Challenges, Recent Advances, and Future Directions,

Reference 3

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source=pdf_text observed=2026-08-11T00:27:13.203904Z digest=sha256:3415a5285d2731ef31ce02a81780c562224c011d71812364687c10ed41806d82

Observation e0e3bd33-8e1d-48e5-8243-37e25d9da7a1 · outbound

This paper cites FedTD3: An Accelerated Learning Approach for UA V Trajectory Planning,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning FedTD3: An Accelerated Learning Approach for UA V Trajectory Planning,

Reference 4

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.207921Z digest=sha256:527400f32b8c71f77a08ff2d5350d2eb968f96fd7e2681265bb61fc161544abe

Observation f7368142-bbc3-421e-abca-9da4c17d2acb · outbound

This paper cites Forget to Improve: On-Device LLM-Agent Continual Learning via Budget-Curated Memory.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Forget to Improve: On-Device LLM-Agent Continual Learning via Budget-Curated Memory

Reference 5

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local_arxiv, observed 2026-08-11T00:27:13.657813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.211545Z digest=sha256:c28f959d934d3466c7aa6a2938b2c61118ef06ba428b98fa559433762fbfe23e

Observation 96dfce72-aa74-4903-81e9-f2a136299477 · outbound

This paper cites CrystalMem: Elastic Memory for Self-Evolving LLM Agents via Knowledge Crystallization.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning CrystalMem: Elastic Memory for Self-Evolving LLM Agents via Knowledge Crystallization

Reference 6

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.215464Z digest=sha256:9fa1b3aa6ac3b51bf2be5f2e895883cabd71df55e03201255c02b8b772818da0

Observation 74146570-9dc0-466a-a573-bea85525bd90 · outbound

This paper cites FedMultimodal: A Benchmark For Multimodal Federated Learning.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning FedMultimodal: A Benchmark For Multimodal Federated Learning

Reference 7

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source=pdf_text observed=2026-08-11T00:27:13.219552Z digest=sha256:085f614cace5ee56be2bc4a9125ba79867124c2177c3746e18e01372d807b4ae

Observation f3dc637e-e3c0-4057-b29b-722ccbde1545 · outbound

This paper cites Towards Multi-Modal Transformers in Federated Learning,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Towards Multi-Modal Transformers in Federated Learning,

Reference 8

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source=pdf_text observed=2026-08-11T00:27:13.223264Z digest=sha256:1e98b6c2915b75d34d153add501c9089d1b465e87338af2642d90a8b4b6e668f

Observation 47ff9598-66a1-4ea6-9916-eb6b472dcd87 · outbound

This paper cites R- ACP: Real-Time Adaptive Collaborative Perception Leveraging Robust Task-Oriented Communications,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning R- ACP: Real-Time Adaptive Collaborative Perception Leveraging Robust Task-Oriented Communications,

Reference 9

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source=pdf_text observed=2026-08-11T00:27:13.226501Z digest=sha256:3c3fe8c67dee059cbdabbd4786ca849436ae04e85280b7d1f88c2295214beeb4

Observation 2df2fdf0-de1c-45e2-8ff1-831685684723 · outbound

This paper cites Shared Spatial Memory Through Predictive Coding,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Shared Spatial Memory Through Predictive Coding,

Reference 10

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source=pdf_text observed=2026-08-11T00:27:13.229934Z digest=sha256:fa408522da86393aa6fa032595cfefa514a817f4717d3b9530e78d5aa1afab89

Observation 68bfe100-4448-42ab-87e6-828963d0826d · outbound

This paper cites ST-Hybrid: Dynamic Graph Learning with Multi- Scale Spatio-Temporal Attention for Traffic Forecasting,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning ST-Hybrid: Dynamic Graph Learning with Multi- Scale Spatio-Temporal Attention for Traffic Forecasting,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.233370Z digest=sha256:d227fc525e4c3033153dca75d3b2db96aaa3d6eb172534a78dca231d96fdd124

Observation 69bc90df-8ac1-4ce2-a4d5-703687d674cc · outbound

This paper cites PRISM: Exposing and Resolving Spurious Isolation in Federated Multimodal Continual Learning.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning PRISM: Exposing and Resolving Spurious Isolation in Federated Multimodal Continual Learning

Reference 12

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source=pdf_text observed=2026-08-11T00:27:13.237284Z digest=sha256:e8c59c4e50d57c02a01c29ff302575c6b4cbd4ca36b6a7ff92f805d650f08002

Observation 72aad84b-25ae-43d5-b305-0fe30264cf57 · outbound

This paper cites Federated Learning Based on Dynamic Regularization,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Federated Learning Based on Dynamic Regularization,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.240957Z digest=sha256:53ffa5e3653f1c51cb3fe2d9fbce69ab662dbaf1f4a95238683745147b351657

Observation 6b6aca07-95fc-445e-9631-6fa28551f316 · outbound

This paper cites FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to System Heterogeneity,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to System Heterogeneity,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.244689Z digest=sha256:20b640edf3f63a3e82d97286fe3880ae9d0eb0321c81146925027892f7a98e57

Observation ad9f81ba-c8a7-4700-a0aa-663dde3a1021 · outbound

This paper cites Adaptive Federated Optimization,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Adaptive Federated Optimization,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.248086Z digest=sha256:b38e80286b27e0b2c3398a7f3e2d4c3dbfff7e0dade22c3a6df7a0c037369278

Observation 686e8460-0b32-45ed-9c92-79f28078ddc4 · outbound

This paper cites FedBABU: Toward Enhanced Represen- tation for Federated Image Classification,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning FedBABU: Toward Enhanced Represen- tation for Federated Image Classification,

Reference 16

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.251335Z digest=sha256:f8922ed5597d904eeb245410f51c0371a0cb202f2371bec1aac895282a5958ca

Observation edfbd1d1-cf51-453d-94b1-62e79887c41b · outbound

This paper cites Model-Contrastive Federated Learning,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Model-Contrastive Federated Learning,

Reference 17

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.254580Z digest=sha256:1accb3d70c34213d08bdaa08de6f150c87b09ad99153281eab8052b4ddf998fb

Observation 6cabafcb-16a0-468f-8d0e-6a502d9715f1 · outbound

This paper cites A Dual- Level Game-Theoretic Approach for Collaborative Learning in UA V- Assisted Heterogeneous Vehicle Networks,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning A Dual- Level Game-Theoretic Approach for Collaborative Learning in UA V- Assisted Heterogeneous Vehicle Networks,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.257856Z digest=sha256:05a2efc3fcaf2150e4406303697e8b69a99dbc7573bffbde47badf31045c9bcd

Observation 59cea408-b9ec-4312-8252-d3afca717d40 · outbound

This paper cites Combating Knowledge Diversity and Catastrophic Forgetting in UA V-Assisted Collaborative Vehicular Learning: A Game-Theoretic Approach,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Combating Knowledge Diversity and Catastrophic Forgetting in UA V-Assisted Collaborative Vehicular Learning: A Game-Theoretic Approach,

Reference 19

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.261089Z digest=sha256:07d2c67d32c67e270989f2082b588d33a6da506b618db0ff59f076225eea6479

Observation 3000394e-7894-47e6-a180-c5da3f207ce0 · outbound

This paper cites Learning to Defend: A Multi-Agent Reinforcement Learning Framework for Stackelberg Security Game in Mobile Edge Computing,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Learning to Defend: A Multi-Agent Reinforcement Learning Framework for Stackelberg Security Game in Mobile Edge Computing,

Reference 20

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.264572Z digest=sha256:a9c0780fbe67d34f206580c8bf38e479d24792014144b03352cc2ef0fa1b06e2

Observation dc18777b-3949-404e-bbd5-de4ca55866a0 · outbound

This paper cites Model-Free Cooperative Optimal Output Regulation for Linear Discrete-Time Multi-Agent Systems Using Reinforcement Learning,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Model-Free Cooperative Optimal Output Regulation for Linear Discrete-Time Multi-Agent Systems Using Reinforcement Learning,

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:27:13.268058Z digest=sha256:3964625a8eac643b788392adf2819566700f8487bdc544ad15e30fc15398b778

Observation 03065d72-51a2-44af-afd1-e877176907d6 · outbound

This paper cites FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization,

Reference 22

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.271240Z digest=sha256:e2e6493868c08f283d71637c19cc6f2ddc77ba4f9417601edbaa7ed92f7c149c

Observation 83ad6585-7338-4030-ac00-78ec4e2da1f2 · outbound

This paper cites Federated Learning: Strategies for Improving Communication Efficiency.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Federated Learning: Strategies for Improving Communication Efficiency

Reference 23

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source=pdf_text observed=2026-08-11T00:27:13.274459Z digest=sha256:b7ca73412595bf7fe51a9c88d90eba619870b7822dd1f5c2e48aee33c42dd38d

Observation 782e0705-4e17-473d-88f5-9a86d665987f · outbound

This paper cites Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge,

Reference 24

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.278246Z digest=sha256:3114bd40087c007ba30efb4cfa3b8fa184aecfa449379b3c646f148ced30efb0

Observation 822e2e75-6fbc-444b-b7e8-e9d9f62732f0 · outbound

This paper cites Enhancing Vehic- ular Platooning With Wireless Federated Learning: A Resource-Aware Control Framework,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Enhancing Vehic- ular Platooning With Wireless Federated Learning: A Resource-Aware Control Framework,

Reference 25

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source=pdf_text observed=2026-08-11T00:27:13.281574Z digest=sha256:293096023f0678eef2e6fd00551fe5feb55fcf6039b7276d689ef57b14349889

Observation 3e9047d2-4f3c-4dee-84b3-a6c0c3998971 · outbound

This paper cites A Fast UA V Tra- jectory Planning Framework in RIS-Assisted Communication Systems With Accelerated Learning via Multithreading and Federating,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning A Fast UA V Tra- jectory Planning Framework in RIS-Assisted Communication Systems With Accelerated Learning via Multithreading and Federating,

Reference 26

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:27:13.284877Z digest=sha256:5cbea19fa9f3e36df0436feadc86eeebc9c79f74b5006f4449bedfed170c8494

Observation 5d9e68c0-3f7c-4c0d-a007-205a2311d250 · outbound

This paper cites ‘X of Information’ Continuum: A Survey on AI-Driven Multi-Dimensional Metrics for Next-Generation Net- worked Systems,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning ‘X of Information’ Continuum: A Survey on AI-Driven Multi-Dimensional Metrics for Next-Generation Net- worked Systems,

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.288136Z digest=sha256:c8ce827ee0fbcc161bd12246ac19f8b8ac551eb24e406915dc907761aa287827

Observation b834caeb-e8de-4db9-a8e4-886d02275d48 · outbound

This paper cites AoI-Aware Resource Management for Smart Health via Deep Reinforcement Learning,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning AoI-Aware Resource Management for Smart Health via Deep Reinforcement Learning,

Reference 28

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source=pdf_text observed=2026-08-11T00:27:13.291603Z digest=sha256:4dc91c5ee2db602ec28d5cbe2b2b43d69290585e60d1e4bb2a78f722ccb43fbe

Observation 3dc894d5-1658-4ce5-a7e7-79be921ecfbd · outbound

This paper cites Transformer-Based Dynamic Resource Allocation for Multi-Carrier NOMA Systems,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Transformer-Based Dynamic Resource Allocation for Multi-Carrier NOMA Systems,

Reference 29

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source=pdf_text observed=2026-08-11T00:27:13.294833Z digest=sha256:691a16e81b6ba0101916b979cb786076b9d48aafe0b529bc10674390675dfd17

Observation 15307893-618e-4271-8bf1-273412695183 · outbound

This paper cites Securing Smart Agriculture with Communication-Efficient Federated Unlearning,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Securing Smart Agriculture with Communication-Efficient Federated Unlearning,

Reference 30

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raw_fallback, observed 2026-08-11T00:27:13.830750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.298593Z digest=sha256:31dec7f3eda5203deca1933630fdd174aa828908ce1e73b2cc0f376f759bacd4

Observation 25e09f69-0916-4aa7-b843-c972edbe5fd4 · outbound

This paper cites Reinforcement Learning- Based Energy-Aware Coverage Path Planning for Precision Agriculture,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Reinforcement Learning- Based Energy-Aware Coverage Path Planning for Precision Agriculture,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.301967Z digest=sha256:21d30d3b789c2bb850241b0bcbd676f28b0730c979cbd401015cc7af026f20e5

Observation d8f3efe6-b2db-4e2f-a476-43cc1f1341f5 · outbound

This paper cites A Stochastic Geometry-Based Analysis of SWIPT-Assisted Underlaid Device-to-Device Energy Har- vesting,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning A Stochastic Geometry-Based Analysis of SWIPT-Assisted Underlaid Device-to-Device Energy Har- vesting,

Reference 32

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:27:13.305205Z digest=sha256:0c452b72d924ef5fa2a6ae005615303860484cae7500f625296472fd91666245

Observation 0ea654fa-9d4d-40ec-a825-7b6af704e198 · outbound

This paper cites A Fault-Tolerant and Energy-Efficient Design of a Network Switch Based on a Quantum- Based Nano-Communication Technique,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning A Fault-Tolerant and Energy-Efficient Design of a Network Switch Based on a Quantum- Based Nano-Communication Technique,

Reference 33

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source=pdf_text observed=2026-08-11T00:27:13.308771Z digest=sha256:5d0f958e4e1225979dcd3e8d30f3b3461003633988289fdc8077091806a59cbb

Observation 82cbf58d-2232-4bbf-958a-8bb8c9c298b8 · outbound

This paper cites Inference-Time Budget Control for LLM Search Agents.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Inference-Time Budget Control for LLM Search Agents

Reference 34

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source=pdf_text observed=2026-08-11T00:27:13.312170Z digest=sha256:7acd0a5d26c55c01e850f4902ef214f5fccb7a116bfbd4a85bf6ae9c24b4c99f

Observation f04f0b1d-2c2b-4237-be54-acc5ce29123a · outbound

This paper cites FedMFS: Federated Multimodal Fusion Learning with Selective Modality Communication.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning FedMFS: Federated Multimodal Fusion Learning with Selective Modality Communication

Reference 35

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source=pdf_text observed=2026-08-11T00:27:13.316024Z digest=sha256:257ae0cc5875c3c1daf1619a19efa9e82e1078a83a1f3f3862901a8cbb3bc5be

Observation a6a8babc-5c83-4a8e-b0c7-cff0ccf7ab54 · outbound

This paper cites RELIEF: Turning Missing Modalities into Training Acceleration for Federated Learning on Heterogeneous IoT Edge.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning RELIEF: Turning Missing Modalities into Training Acceleration for Federated Learning on Heterogeneous IoT Edge

Reference 36

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source=pdf_text observed=2026-08-11T00:27:13.319869Z digest=sha256:6bd7746d3502d705637cb0a58ec92aa1041cfd00c10bc70df5346a912bc40162

Observation 3a076241-8bc1-4190-bd3e-12d0ae02a5f6 · outbound

This paper cites EASE: Federated Multimodal Unlearning via Entanglement-Aware Anchor Closure.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning EASE: Federated Multimodal Unlearning via Entanglement-Aware Anchor Closure

Reference 37

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source=pdf_text observed=2026-08-11T00:27:13.323434Z digest=sha256:570ed0f50d9b5241ee4d985b9aa2ec10f1adc754aaaf12d014babb11d1f8f81a

Observation 82668f37-3462-4cf4-a2c4-0c0cded33945 · outbound

This paper cites Oort: Efficient Federated Learning via Guided Participant Selection,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Oort: Efficient Federated Learning via Guided Participant Selection,

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-11T00:27:13.796121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.327205Z digest=sha256:66d3a88e49690f0bf27ec54566b0e8c5f98611bb8d7459b35d45cc5ee772905c

Observation 8b1433a6-dccd-4834-b2ad-818185b59392 · outbound

This paper cites Federated Optimization in Heterogeneous Networks,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Federated Optimization in Heterogeneous Networks,

Reference 39

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raw_fallback, observed 2026-08-11T00:27:13.785619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.330462Z digest=sha256:aae3337b593507de9e64bf30e3ca73eff57c57123fa90a6db0841201158f1852

Observation ce081ccc-1a52-4c37-958d-65f9a8bfb31b · outbound

This paper cites Elastic Aggregation for Federated Optimization,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Elastic Aggregation for Federated Optimization,

Reference 40

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raw_fallback, observed 2026-08-11T00:27:13.774111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.333628Z digest=sha256:4bce48e6d564c0c7b8fb0f953793ba61735943c0da5185d4d8400dd17926c348

Observation 3f6eedd6-0940-4f78-a806-174644bda387 · outbound

This paper cites FedBN: Federated Learning on Non-IID Features via Local Batch Normalization,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning FedBN: Federated Learning on Non-IID Features via Local Batch Normalization,

Reference 41

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source=pdf_text observed=2026-08-11T00:27:13.336998Z digest=sha256:701285cf426ab28f5d42b5f4466f23b0238da144f677c2789e4d145afdff367f

Observation 0d332513-5889-4215-9a45-f22e34c83cd3 · outbound

This paper cites Exploiting Shared Representations for Personalized Federated Learning,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Exploiting Shared Representations for Personalized Federated Learning,

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-11T00:27:13.757366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.340501Z digest=sha256:5224fc4431445ac27e19d2df832b16e1349fd7fd7bb7bc54f79284721d94f691

Observation 5319fc69-7660-45c2-a72e-fbb878b36745 · outbound

This paper cites Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relation- ships,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relation- ships,

Reference 43

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raw_fallback, observed 2026-08-11T00:27:13.746005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.344127Z digest=sha256:2e121e303aa88818a4fd733e5155ed020f8c470e56763ca22406df19e817095e

Observation bdc7ce62-b258-42ac-a3fa-4469861e8fb6 · outbound

This paper cites FedSR: A Simple and Effec- tive Domain Generalization Method for Federated Learning,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning FedSR: A Simple and Effec- tive Domain Generalization Method for Federated Learning,

Reference 44

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.347673Z digest=sha256:d086540c67892238b21cce03df7733be7418ff21851a8aae625ecaca0659f7c4

Observation 6cd2dc63-d841-4ec0-b227-456efce2544a · outbound

This paper cites A Review of Continual Learning in Edge AI,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning A Review of Continual Learning in Edge AI,

Reference 45

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source=pdf_text observed=2026-08-11T00:27:13.351120Z digest=sha256:a9e118ec04ce298c80e1b7ab1e6f99cc8e7775a81b4d4f29d6b085b12fb633aa

Observation e099a017-8de9-4e32-80c9-7f96e8d8fa1a · outbound

This paper cites Lifecycle-Aware Federated Continual Learning in Mobile Autonomous Systems.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Lifecycle-Aware Federated Continual Learning in Mobile Autonomous Systems

Reference 46

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source=pdf_text observed=2026-08-11T00:27:13.354399Z digest=sha256:02ee3958461ff06b40ff4b8e469a07b7d9448fbddbff518b6e831030df5fd033

Observation b4154fd5-c1db-4697-9ae3-e18e0f90b3ec · outbound

This paper cites From Alpha to Omega: Lifecycle- Aware Forgetting Defense in Federated Continual Learning for Planetary Exploration,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning From Alpha to Omega: Lifecycle- Aware Forgetting Defense in Federated Continual Learning for Planetary Exploration,

Reference 47

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verified fuzzy
raw_fallback, observed 2026-08-11T00:27:13.718076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.357940Z digest=sha256:6520f8f374f52ce56675de47075982eb0eee123f26cfc36f7bbf279c28e96af0

Observation f63f51cb-4bab-47a8-a10d-5ed54bddb9bd · outbound

This paper cites nuScenes: A Multimodal Dataset for Autonomous Driving,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning nuScenes: A Multimodal Dataset for Autonomous Driving,

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-11T00:27:13.706804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.361492Z digest=sha256:d9de2fe01ad35e0b37957e7cbd596e4648ee4d8a6747027eccb0ff25cff1849b

Observation 468bfd4f-92c4-484e-b79b-df20e37e21cf · outbound

This paper cites Real-Time Intelligent Healthcare Enabled by Federated Digital Twins With AoI Optimization,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Real-Time Intelligent Healthcare Enabled by Federated Digital Twins With AoI Optimization,

Reference 49

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source=pdf_text observed=2026-08-11T00:27:13.364838Z digest=sha256:9aaa956818ec221f5e1da43b31159ab36b2e552a94d9f06fbf7f27d95213793b

Observation aae96bef-97d4-4813-8438-e5c88f9cfb83 · outbound

This paper cites Application-Aware Twin-in-the-Loop Planning for Federated Split Learning over Wireless Edge Networks.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Application-Aware Twin-in-the-Loop Planning for Federated Split Learning over Wireless Edge Networks

Reference 50

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no resolver link, observed 2026-08-11T00:27:13.368208Z

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source=pdf_text observed=2026-08-11T00:27:13.368208Z digest=sha256:d63f9490e737ffc1e96d426440fd09b5b01e2aab7b911f0317b519b39dd269e9

Observation a4a69195-e77f-486c-944e-cb312089c350 · outbound

This paper cites SCALE: Sensitivity-Aware Federated Unlearning with Information Freshness Optimization for Mobile Edge Computing,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning SCALE: Sensitivity-Aware Federated Unlearning with Information Freshness Optimization for Mobile Edge Computing,

Reference 51

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verified fuzzy
raw_fallback, observed 2026-08-11T00:27:13.689949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.371510Z digest=sha256:2309650c9ec40e8b7182c942e5b13b58d869b92e06bd87d9fe71c1ac6d8839e4

Observation 9c4d5e9b-2245-49a1-b328-9393ba35b3db · outbound

This paper cites On Nonlinear Fractional Programming,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning On Nonlinear Fractional Programming,

Reference 52

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verified fuzzy
raw_fallback, observed 2026-08-11T00:27:13.679087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.375071Z digest=sha256:6cba5b4df851a618b529905e4f6717040faa34591baf5f9ab5dec4b6cb82445f

Observation a6cc7348-e24e-4337-82b7-c247a2338d8a · outbound

This paper cites Bounds for Certain Multiprocessing Anomalies,.

FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning Bounds for Certain Multiprocessing Anomalies,

Reference 53

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verified fuzzy
raw_fallback, observed 2026-08-11T00:27:13.668983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T00:27:13.378355Z digest=sha256:067b3687c482f75dd0ad64cb41ff5984ef1913db2e5c0907d2e6bcfe6381e906

Pith citing papers

No inbound Pith citation observations are available.