Paper Citation Record · LEDGER

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding

As of 21 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2412.20467.

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

pith.paper-citation-record.v1
2412.20467 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:24:08.169151Z

measured 24 of 24 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:24:08.074934Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T23:24:08.237698Z

Reference resolution

23 of 23 outbound references displayed

verified exact0
verified fuzzy16
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4ab2acca-35be-487c-a957-65f5826c5a05 · outbound

This paper cites an unresolved cited work.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:24:08.549471Z

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.

Observation 0b0d99d3-7e27-4747-8d9b-7fb786d5783a · outbound

This paper cites an unresolved cited work.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:24:08.534078Z

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.

Observation 08c9b113-dbef-42c3-9466-64fbe24eec2d · outbound

This paper cites Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding

Reference 3

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T23:24:08.244988Z

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.

Observation 47748703-a2a0-4753-8cd9-91a2c201dbd4 · outbound

This paper cites EncDec As SOTA, we take the EncDec model from Blatt et al.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding EncDec As SOTA, we take the EncDec model from Blatt et al

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.504913Z

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.

Observation 6921115b-dc63-4184-8bb4-2fc96b1483d9 · outbound

This paper cites CallSBERT: Surveillance adaptation Depending on the the flight sector, the amount of surveillance call-signs available might vary.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding CallSBERT: Surveillance adaptation Depending on the the flight sector, the amount of surveillance call-signs available might vary

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.490376Z

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.

Observation 779cf42d-1c9d-42d6-865b-7ca4a1388082 · outbound

This paper cites Fine-tuning on noisy transcripts reduces the noise intro- duced accuracy drop significantly without degrading accuracy levels on clean data.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Fine-tuning on noisy transcripts reduces the noise intro- duced accuracy drop significantly without degrading accuracy levels on clean data

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.475353Z

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.

Observation 1c3b9db5-5ce2-48cd-905b-25fbaf81703a · outbound

This paper cites Survey of Hallucination in Natural Language Generation,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Survey of Hallucination in Natural Language Generation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.367012Z

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.

Observation 60aee96c-6910-4ac4-b7ac-422acea4018d · outbound

This paper cites Iterative learning of speech recognition models for air traffic control,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Iterative learning of speech recognition models for air traffic control,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.460123Z

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.

Observation f2ba7562-dbe4-43f0-b6e1-de40e497273b · outbound

This paper cites Automatic call sign detection: Matching air surveillance data with air traffic spoken communications,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Automatic call sign detection: Matching air surveillance data with air traffic spoken communications,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.444733Z

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.

Observation b1fe6a93-a737-4d80-b209-68d91318eae1 · outbound

This paper cites EASA Concept Paper: First usable guidance for Level 1 machine learning applications,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding EASA Concept Paper: First usable guidance for Level 1 machine learning applications,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.429971Z

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.

Observation 1ce8b3c2-3d6c-490e-950f-d5c9b53635b0 · outbound

This paper cites The ATCOSIM corpus of non-prompted clean air traffic control speech,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding The ATCOSIM corpus of non-prompted clean air traffic control speech,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.414190Z

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.

Observation 051875b4-6ca2-4ca0-95c1-df1b8e687785 · outbound

This paper cites The Airbus Air Traffic Control Speech Recognition 2018 Challenge: Towards ATC Automatic Transcription and Call Sign Detection,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding The Airbus Air Traffic Control Speech Recognition 2018 Challenge: Towards ATC Automatic Transcription and Call Sign Detection,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.398452Z

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.

Observation 74261bca-6c58-40b6-8232-7e144ca01099 · outbound

This paper cites Automatic Processing Pipeline for Collecting and Annotating Air-Traffic V oice Communication Data,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Automatic Processing Pipeline for Collecting and Annotating Air-Traffic V oice Communication Data,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.382407Z

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.

Observation 44c6528b-e7d9-44b0-ba9d-34cf13352242 · outbound

This paper cites an unresolved cited work.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:24:08.519525Z

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.

Observation 5f9ff423-f40e-4f07-9bff-d27af6fe584f · outbound

This paper cites Call- Sign Recognition and Understanding for Noisy Air-Traffic Tran- scripts Using Surveillance Information,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Call- Sign Recognition and Understanding for Noisy Air-Traffic Tran- scripts Using Surveillance Information,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.351326Z

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.

Observation c9275def-97aa-4358-8de6-ccc38a9ed216 · outbound

This paper cites CRIM’s Speech Transcription and Call Sign Detection System for the ATC Airbus Challenge task,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding CRIM’s Speech Transcription and Call Sign Detection System for the ATC Airbus Challenge task,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.334216Z

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.

Observation 590a3a02-5ab6-4f79-bdd8-1c2688207735 · outbound

This paper cites Improving callsign recognition with air-surveillance data in air-traffic communication.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Improving callsign recognition with air-surveillance data in air-traffic communication

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:08.140615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a33892c3-64c5-4858-b1dd-a6c6e2b680b0 · outbound

This paper cites Robust Command Recognition for Lithuanian Air Traffic Control Tower Utter- ances,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Robust Command Recognition for Lithuanian Air Traffic Control Tower Utter- ances,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.318135Z

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.

Observation 86858187-1b76-4667-a962-6bd68f78216d · outbound

This paper cites A context- aware language model to improve the speech recognition in air traffic control,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding A context- aware language model to improve the speech recognition in air traffic control,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.302009Z

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.

Observation 16275a9b-4885-47ae-93c8-aa2231eeb475 · outbound

This paper cites Machine learning of controller command prediction models from recorded radar data and controller speech utterances,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Machine learning of controller command prediction models from recorded radar data and controller speech utterances,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.286163Z

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.

Observation 43d1ae27-a224-4dbf-971f-e225e7edcf27 · outbound

This paper cites Sentence-bert: Sentence embeddings using siamese bert-networks,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Sentence-bert: Sentence embeddings using siamese bert-networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:08.270910Z

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.

Observation 6a69b272-83f6-41aa-a1f6-d8fdc392b66b · outbound

This paper cites BERT: pre-training of deep bidirectional transformers for language understanding,.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding BERT: pre-training of deep bidirectional transformers for language understanding,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:08.169151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0757acf-00fe-4d5d-a5c6-82c8c29c80e5 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Utilizing Multimodal Data for Edge Case Robust Call-sign Recognition and Understanding Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:08.163895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 08c9b113-dbef-42c3-9466-64fbe24eec2d · inbound