Paper Citation Record · LEDGER

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures

As of 16 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2605.01776.

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

pith.paper-citation-record.v1
2605.01776 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-09T16:44:17.589114Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

33 of 33 outbound references displayed

verified exact4
verified fuzzy29
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4f3fed5c-1d51-4383-a9fb-f7b563cd437e · outbound

This paper cites ServiceAnomaly: An anomaly detection approach in microservices using distributed traces and profiling metrics.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures ServiceAnomaly: An anomaly detection approach in microservices using distributed traces and profiling metrics

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.015299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1d17a402-102a-4001-b916-472133401545 · outbound

This paper cites Anomaly detection in microservice environments using distributed tracing data analysis and NLP.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Anomaly detection in microservice environments using distributed tracing data analysis and NLP

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.021636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 157e1090-f6df-4276-9b07-b07a695c2f73 · outbound

This paper cites Root cause analysis of failures in microservices through causal discovery.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Root cause analysis of failures in microservices through causal discovery

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.027706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f42503e0-598b-408b-8bb2-42225a9ebe9a · outbound

This paper cites Microirc: Instance-level root cause localization for microservice systems.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Microirc: Instance-level root cause localization for microservice systems

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.077059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation eed7c717-a368-4abd-821c-b7068e21a718 · outbound

This paper cites Anomalous distributed traffic: Detecting cyber security attacks amongst microservices using graph convolutional networks.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Anomalous distributed traffic: Detecting cyber security attacks amongst microservices using graph convolutional networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.081990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 840e8c86-9f01-48da-a522-ac1f961074c7 · outbound

This paper cites Spatiotemporal Risk Representation Learning Using Transformers and Graph Structure.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Spatiotemporal Risk Representation Learning Using Transformers and Graph Structure

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.055912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f6a4371d-bd23-4dde-aa00-ee621ad2ea31 · outbound

This paper cites A Data-Centric Sequential Modeling Framework for Session-Level Decision Intelligence.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures A Data-Centric Sequential Modeling Framework for Session-Level Decision Intelligence

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:24.905476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 732b2525-6608-454e-92d1-5536c3bd68c3 · outbound

This paper cites Cost-Sensitive Mamba Sequence Modeling for Fault Detection in Cloud-Native Microservice Systems.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Cost-Sensitive Mamba Sequence Modeling for Fault Detection in Cloud-Native Microservice Systems

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:24.995856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a5cb8495-ced5-4e05-9f00-bc28b38ec9fd · outbound

This paper cites Deep Learning- Based Uncertainty-Driven Robust Time Series Forecasting for Backend Service Metrics.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Deep Learning- Based Uncertainty-Driven Robust Time Series Forecasting for Backend Service Metrics

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.066424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation df71f584-fd70-4a30-b0fa-160bb3b63bb6 · outbound

This paper cites Stable Fault Diagnosis Under Data Imbalance via Self-Supervised Learning in Industrial IoT.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Stable Fault Diagnosis Under Data Imbalance via Self-Supervised Learning in Industrial IoT

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.044302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9ee32950-8865-4da2-82ac-14c22690236d · outbound

This paper cites Few-Shot Financial Fraud Detection Using Meta-Learning and Large Language Models.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Few-Shot Financial Fraud Detection Using Meta-Learning and Large Language Models

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:24.891643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ced05ce6-598d-4df6-aef9-5b414d5ed5bf · outbound

This paper cites DualShiftNet: Joint Class-Imbalance and Distribution-Shift Aware Learning for Business Risk Prediction.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures DualShiftNet: Joint Class-Imbalance and Distribution-Shift Aware Learning for Business Risk Prediction

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.033719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a04dc2a1-d6a4-477b-af36-4d70029e1e3a · outbound

This paper cites Shared Representation Learning for High-Dimensional Multi-Task Forecasting under Resource Contention in Cloud-Native Backends.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Shared Representation Learning for High-Dimensional Multi-Task Forecasting under Resource Contention in Cloud-Native Backends

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:26:10.010611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e8826821-d64b-4101-8a11-3fce179cd688 · outbound

This paper cites Anomaly Detection in Microservice Environments via Conditional Multiscale GANs and Adaptive Temporal Autoencoders.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Anomaly Detection in Microservice Environments via Conditional Multiscale GANs and Adaptive Temporal Autoencoders

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.096642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 827db25c-dca2-49fd-98d0-0fcd6b681d80 · outbound

This paper cites Real-time anomaly detection using distributed tracing in microservice cloud applications.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Real-time anomaly detection using distributed tracing in microservice cloud applications

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:24.985522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 765230cb-a66a-461d-9250-3e70aeeee1ca · outbound

This paper cites Structured State Representation and Constraint-Guided Policy Learning for Intelligent Business Decision Systems.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Structured State Representation and Constraint-Guided Policy Learning for Intelligent Business Decision Systems

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:24.978257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 68afc916-05cb-4e91-aa0b-3e548cf27954 · outbound

This paper cites Memory-Driven Agent Planning for Long-Horizon Tasks via Hierarchical Encoding and Dynamic Retrieval.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Memory-Driven Agent Planning for Long-Horizon Tasks via Hierarchical Encoding and Dynamic Retrieval

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:24.968733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 03ffb46d-7673-41f5-8422-759f6f1dfac0 · outbound

This paper cites MIN-Trust: A Minimum Necessary Information Trust Orchestration Framework for Multi-Agent Collaboration.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures MIN-Trust: A Minimum Necessary Information Trust Orchestration Framework for Multi-Agent Collaboration

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.008989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2f24ae8e-8e6a-44fb-b511-1d653806e413 · outbound

This paper cites Integrating Large Language Models with Cloud-Native Observability for Automated Root Cause Analysis and Remediation.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Integrating Large Language Models with Cloud-Native Observability for Automated Root Cause Analysis and Remediation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.061342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a4849035-e5e8-4bf8-9d79-39afe7601f5b · outbound

This paper cites FlashServe: Cost-Efficient Serverless Inference Scheduling for Large Language Models via Tiered Memory Management and Predictive Autoscaling.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures FlashServe: Cost-Efficient Serverless Inference Scheduling for Large Language Models via Tiered Memory Management and Predictive Autoscaling

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.050132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 709cf442-69e2-4c40-82d5-c463426d3849 · outbound

This paper cites A Multi-Agent Coding Assistant for Cloud-Native Development: From Requirements to Deployable Microservices.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures A Multi-Agent Coding Assistant for Cloud-Native Development: From Requirements to Deployable Microservices

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.002900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 59c6d0bc-fc04-4dca-9f50-ef2cab0d877a · outbound

This paper cites Deep Learning Approach for Protocol Anomaly Detection Using Status Code Sequences.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Deep Learning Approach for Protocol Anomaly Detection Using Status Code Sequences

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.092081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f291f326-496d-4ab2-9437-c52034c0a675 · outbound

This paper cites Stabilizing Cloud Elastic Scaling with Risk-Constrained Reinforcement Learning Under Workload Drift.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Stabilizing Cloud Elastic Scaling with Risk-Constrained Reinforcement Learning Under Workload Drift

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.106100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 512b15e4-bbbb-4e69-be26-642e860e53a1 · outbound

This paper cites DeepServe: SLO-Aware and Cost-Aware Elastic Scheduling for Serverless Multi-Tenant LLM Inference.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures DeepServe: SLO-Aware and Cost-Aware Elastic Scheduling for Serverless Multi-Tenant LLM Inference

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.101248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 30e6678b-c8d3-463d-8a14-14220a6aaf8f · outbound

This paper cites TokenFlow: Token-Level GPU Sharing and Adaptive Scheduling for Multi-Model Concurrent LLM Inference.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures TokenFlow: Token-Level GPU Sharing and Adaptive Scheduling for Multi-Model Concurrent LLM Inference

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.087437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d6cfe5ed-c3e0-4119-b377-388aa571bcb1 · outbound

This paper cites Deep Reinforcement Learning Guided by Game-Theoretic Structure for Multi-Agent Resource Allocation and Scheduling.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Deep Reinforcement Learning Guided by Game-Theoretic Structure for Multi-Agent Resource Allocation and Scheduling

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.072023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b50fb326-eb6d-4d3f-afb4-1d44a0b1b380 · outbound

This paper cites Graph Neural AI with Temporal Dynamics for Comprehensive Anomaly Detection in Microservices.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Graph Neural AI with Temporal Dynamics for Comprehensive Anomaly Detection in Microservices

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:26:10.025557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5e214499-c817-4f13-9772-bb31e33c86d4 · outbound

This paper cites TraceGra: A trace-based anomaly detection for microservice using graph deep learning.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures TraceGra: A trace-based anomaly detection for microservice using graph deep learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:27:16.372475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d4124c70-13e6-430c-999d-453226c71729 · outbound

This paper cites Root cause analysis in microservice using neural granger causal discovery.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Root cause analysis in microservice using neural granger causal discovery

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:27:16.785852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fa2bea62-aa77-4194-a672-3720076afe7b · outbound

This paper cites Sleuth: A trace-based root cause analysis system for large-scale microservices with graph neural networks.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Sleuth: A trace-based root cause analysis system for large-scale microservices with graph neural networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:27:16.790727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 61bd06cd-9f03-4929-991c-20b7901d15c4 · outbound

This paper cites CHASE: A Causal Hypergraph based Framework for Root Cause Analysis in Multimodal Microservice Systems.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures CHASE: A Causal Hypergraph based Framework for Root Cause Analysis in Multimodal Microservice Systems

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:26:10.047561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6cfd15e7-6492-409b-8be8-3f2718924caa · outbound

This paper cites Online multi-modal root cause analysis.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures Online multi-modal root cause analysis

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:26:10.064348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 213891d8-54fc-4b91-a2b2-81fc9a5583d8 · outbound

This paper cites CPU-Only Spatiotemporal Anomaly Detection in Microservice Systems via Dynamic Graph Neural Networks and LSTM.

Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures CPU-Only Spatiotemporal Anomaly Detection in Microservice Systems via Dynamic Graph Neural Networks and LSTM

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T00:31:25.038913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

No inbound Pith citation observations are available.