Paper Citation Record · LEDGER

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning

As of 18 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2505.00299.

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

pith.paper-citation-record.v1
2505.00299 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:49:08.759598Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:37:04.381440Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T18:37:04.460146Z

Reference resolution

30 of 30 outbound references displayed

verified exact1
verified fuzzy21
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 54abd207-ec41-4f4b-abd1-4705c24bf253 · outbound

This paper cites Facilitating the migration to the microservice architecture via model- driven reverse engineering and reinforcement learning.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Facilitating the migration to the microservice architecture via model- driven reverse engineering and reinforcement learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:09.032147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 540acdcd-ec98-458c-866b-2f8dad676c40 · outbound

This paper cites Online microservice orchestration for IoT via multiobjective deep reinforcement learning.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Online microservice orchestration for IoT via multiobjective deep reinforcement learning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:09.023380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 270319f8-6c67-4df9-a9c6-0b35bc46a8bd · outbound

This paper cites Root cause analysis for microservice systems via hierarchical reinforcement learning from human feedback.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Root cause analysis for microservice systems via hierarchical reinforcement learning from human feedback

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:09.015067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d19964be-b395-4a6f-8e6a-52e4de2b2c6b · outbound

This paper cites Efficient microservice deployment in the edge-cloud networks with policy- gradient reinforcement learning.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Efficient microservice deployment in the edge-cloud networks with policy- gradient reinforcement learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:09.006554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation be05ff1a-621b-4f13-962f-e0d1c6cc0d25 · outbound

This paper cites A Deep Learning Framework for Boundary-Aware Semantic Segmentation.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning A Deep Learning Framework for Boundary-Aware Semantic Segmentation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T04:49:08.686057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b3d9d0f-6a76-4496-be24-5f7c3dcd50e0 · outbound

This paper cites A Self-Supervised Vision Transformer Approach for Dermatological Image Analysis.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning A Self-Supervised Vision Transformer Approach for Dermatological Image Analysis

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.998353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b6177a2a-e1a1-40ad-9223-61dcc8225887 · outbound

This paper cites Optimized Unet with Attention Mechanism for Multi-Scale Semantic Segmentation.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Optimized Unet with Attention Mechanism for Multi-Scale Semantic Segmentation

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-16T04:49:08.836937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d99dd32d-31a1-43b6-9756-42a077626c2b · outbound

This paper cites Generative UI Design with Diffusion Models: Exploring Automated Interface Creation and Human-Computer Interaction.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Generative UI Design with Diffusion Models: Exploring Automated Interface Creation and Human-Computer Interaction

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.990260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 483ff54a-6a27-4e8e-b58b-29c65b880c00 · outbound

This paper cites User Intent Prediction and Response in Human- Computer Interaction via BiLSTM.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning User Intent Prediction and Response in Human- Computer Interaction via BiLSTM

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.981705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1e88e1ad-5b9f-45e3-b959-3a12dbd6b05f · outbound

This paper cites Efficient Compression of Large Language Models with Distillation and Fine-Tuning.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Efficient Compression of Large Language Models with Distillation and Fine-Tuning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.972885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 05dd7722-f4d6-4b7a-9f98-68e61b42c4ea · outbound

This paper cites Pre-trained Language Models and Few-shot Learning for Medical Entity Extraction.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Pre-trained Language Models and Few-shot Learning for Medical Entity Extraction

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T04:49:08.704039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5af59d4d-1d89-4010-8b99-93827f85c1ff · outbound

This paper cites Deep Learning for Cross-Domain Recommendation with Spatial-Channel Attention.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Deep Learning for Cross-Domain Recommendation with Spatial-Channel Attention

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.963711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3f532c7e-3c36-49a6-9c33-ef11d052c964 · outbound

This paper cites Distributed Network Traffic Scheduling via Trust-Constrained Policy Learning Mechanisms.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Distributed Network Traffic Scheduling via Trust-Constrained Policy Learning Mechanisms

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.954923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f173c550-21b5-4116-b310-3f5e8f2404f9 · outbound

This paper cites Federated Learning for Cross-Domain Data Privacy: A Distributed Approach to Secure Collaboration.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Federated Learning for Cross-Domain Data Privacy: A Distributed Approach to Secure Collaboration

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T04:49:08.712711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7d2507f-40a1-45ab-a80c-67023034d573 · outbound

This paper cites Single-Device Human Activity Recognition Based on Spatiotemporal Feature Learning Networks.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Single-Device Human Activity Recognition Based on Spatiotemporal Feature Learning Networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.946284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 66b4848c-821a-4f2e-8e24-c9190dd97043 · outbound

This paper cites A Deep Learning Approach to Interface Color Quality Assessment in HCI.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning A Deep Learning Approach to Interface Color Quality Assessment in HCI

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T04:49:08.719200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa529bb4-20db-49c2-a580-eee2b22ef919 · outbound

This paper cites Human-Computer Interaction in Smart Devices: Leveraging Sentiment Analysis and Knowledge Graphs for Personalized User Experiences.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Human-Computer Interaction in Smart Devices: Leveraging Sentiment Analysis and Knowledge Graphs for Personalized User Experiences

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.937785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f9496c1b-dfd4-4c40-beb8-67fb47ac20ec · outbound

This paper cites Context-Aware Adaptive Sampling for Intelligent Data Acquisition Systems Using DQN.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Context-Aware Adaptive Sampling for Intelligent Data Acquisition Systems Using DQN

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T04:49:08.724910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4997277f-6c60-4c40-98fa-bb72f7017ead · outbound

This paper cites Addressing Class Imbalance with Probabilistic Graphical Models and Variational Inference.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Addressing Class Imbalance with Probabilistic Graphical Models and Variational Inference

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T04:49:08.728146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8e359de-d6e9-4dcb-b6d5-5cd464f87d0f · outbound

This paper cites Social Network User Profiling for Anomaly Detection Based on Graph Neural Networks.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Social Network User Profiling for Anomaly Detection Based on Graph Neural Networks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T04:49:08.731291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1bd02eb-595a-4a96-b6e2-b543c147b352 · outbound

This paper cites Transformer-Based Structural Anomaly Detection for Video File Integrity Assessment.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Transformer-Based Structural Anomaly Detection for Video File Integrity Assessment

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.928109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 48c79814-7820-457d-a61e-466a2748f6d8 · outbound

This paper cites Contrastive and Variational Approaches in Self-Supervised Learning for Complex Data Mining.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Contrastive and Variational Approaches in Self-Supervised Learning for Complex Data Mining

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T04:49:08.737405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17b5e21f-ea75-4af9-aef4-754ebf979f32 · outbound

This paper cites Analysis and clustering of workload in Google cluster trace based on resource usage.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Analysis and clustering of workload in Google cluster trace based on resource usage

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.919730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 26f66494-519e-4359-b2d4-8eb891bb8833 · outbound

This paper cites An effective deep learning architecture leveraging BIRCH clustering for resource usage prediction of heterogeneous machines in cloud data center.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning An effective deep learning architecture leveraging BIRCH clustering for resource usage prediction of heterogeneous machines in cloud data center

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.911311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9dc1b7b7-b395-426d-aa3e-234cf7b5516a · outbound

This paper cites Literature survey: statistical characteristics of Google cluster trace.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Literature survey: statistical characteristics of Google cluster trace

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.901985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation aa291889-dc87-4b72-8b6a-7ec0e9527fe6 · outbound

This paper cites A survey on microservices architecture: Principles, patterns and migration challenges.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning A survey on microservices architecture: Principles, patterns and migration challenges

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.892475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f0406bee-61ff-4f90-b574-c8e7b8293fca · outbound

This paper cites Optimizing Cloud Performance: A Microservice Scheduling Strategy for Enhanced Fault- Tolerance, Reduced Network Traffic, and Lower Latency.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Optimizing Cloud Performance: A Microservice Scheduling Strategy for Enhanced Fault- Tolerance, Reduced Network Traffic, and Lower Latency

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.882184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 813534de-5b04-439f-9008-197dc1422d96 · outbound

This paper cites DoME: Dew computing based microservice execution in mobile edge using Q-learning.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning DoME: Dew computing based microservice execution in mobile edge using Q-learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.873318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 73aa56aa-284c-4f9d-b736-821c66f2f40b · outbound

This paper cites D3QN-based secure scheduling of microservice workflows in cloud environments.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning D3QN-based secure scheduling of microservice workflows in cloud environments

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.864119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 64bd30b3-1379-4720-9410-0519fc8bfefe · outbound

This paper cites Model pruning-enabled federated split learning for resource-constrained devices in artificial intelligence empowered edge computing environment.

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning Model pruning-enabled federated split learning for resource-constrained devices in artificial intelligence empowered edge computing environment

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:49:08.855253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation 6c4d290c-2d9b-43a7-acb3-957ccd3933c8 · inbound

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning cites this paper.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:37:04.466338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.