Paper Citation Record · LEDGER

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices

As of 31 July 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2605.00351.

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

pith.paper-citation-record.v1
2605.00351 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-09T20:18:38.582291Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-31T06:34:12.847434+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

14 of 14 outbound references displayed

verified exact5
verified fuzzy8
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 94fac0c2-2c7d-4714-bb2b-46241e73652e · outbound

This paper cites Neural controlled differential equations for irregular time series.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Neural controlled differential equations for irregular time series

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T13:29:33.230674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 54f93633-4cf1-4fac-a4dd-252c304f655d · outbound

This paper cites You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:21:05.675423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 0f4ab6bc-e1b4-4c81-b07e-4fce21caf1c5 · outbound

This paper cites Attention bottlenecks for multimodal fusion.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Attention bottlenecks for multimodal fusion

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T13:29:33.227042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 7b6aacb9-ca8a-46b3-924e-88dd275228df · outbound

This paper cites Resilient Routing: Risk-Aware Dynamic Routing in Smart Logistics via Spatiotemporal Graph Learning.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Resilient Routing: Risk-Aware Dynamic Routing in Smart Logistics via Spatiotemporal Graph Learning

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-26T02:15:39.353560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation b0bf428c-c6a9-4906-9f40-1ce38ed2e46b · outbound

This paper cites Dynotears: Structure learning from time-series data.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Dynotears: Structure learning from time-series data

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T13:29:33.213022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 398879da-6cd4-4880-8236-43596fc10348 · outbound

This paper cites Differentiable causal discovery from interventional data.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Differentiable causal discovery from interventional data

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T13:29:33.216553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 792a4147-8a98-477e-b91a-b5c43a2148dc · outbound

This paper cites Self- destructive language model.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Self- destructive language model

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:21:05.618160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation de1c0720-03df-42d8-8fb9-d65e2a6d8245 · outbound

This paper cites Leveraging large lan- guage models: Enhancing retrieval-augmented generation with scann and gemma for superior ai response.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Leveraging large lan- guage models: Enhancing retrieval-augmented generation with scann and gemma for superior ai response

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T13:29:33.219958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 1b336a79-8883-4c17-ba4b-883e72649d0a · outbound

This paper cites Perceiver IO: A General Architecture for Structured Inputs & Outputs.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Perceiver IO: A General Architecture for Structured Inputs & Outputs

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-15T19:47:14.368858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 4bffa1a8-c95f-47d4-ab06-3a0279de7131 · outbound

This paper cites An integrated machine learning and deep learning framework for credit card approval prediction.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices An integrated machine learning and deep learning framework for credit card approval prediction

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T13:29:33.223490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 8c89a634-18c6-46fb-8861-73c1ded4bf5f · outbound

This paper cites Garg,Learning Apache Kafka.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Garg,Learning Apache Kafka

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T13:29:33.234034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation e648cb05-af1b-4360-b3cf-179e4e5d8aa8 · outbound

This paper cites Deep Variational Information Bottleneck.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Deep Variational Information Bottleneck

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:23:00.530339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 8dde789c-52cb-4d10-8a25-a736e03138e3 · outbound

This paper cites Martin Tutek, Fateme Hashemi Chaleshtori, Ana Marasovic, and Yonatan Belinkov.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Martin Tutek, Fateme Hashemi Chaleshtori, Ana Marasovic, and Yonatan Belinkov

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:21:05.627019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 48de7a7a-0baf-48a1-bfca-8cd56a6e9225 · outbound

This paper cites Enhancing educational content matching using transformer models and infonce loss.

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices Enhancing educational content matching using transformer models and infonce loss

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T13:29:33.237553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Pith citing papers

No inbound Pith citation observations are available.