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Paper Citation Record · LEDGER

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering

As of 12 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2411.15372.

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

pith.paper-citation-record.v1
2411.15372 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:25:02.905354Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

50 of 50 outbound references displayed

  • verified exact5
  • verified fuzzy1
  • unresolved44
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 079212d1-5111-473f-82d9-147d39682164 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 1

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unresolved
no resolver link, observed 2026-08-12T14:25:02.624406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.624406Z digest=sha256:92c5c5c7b053cba446bd8759d64759c4a1ab5a0dea4abad92d8ff01fea39ab7f

Observation 06076912-cf4f-4ff4-9d1e-a6e6d9311e23 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 2

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unresolved
raw_fallback, observed 2026-08-12T14:25:04.372592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T14:25:02.630674Z digest=sha256:03148c1be061a352997ee9a52b125b90360fbfdea3ba83b781c8e976ec7a0467

Observation 3f3e040f-3621-41bb-b55c-0942fcf21bdd · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Neural Machine Translation by Jointly Learning to Align and Translate

Reference 3

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no resolver link, observed 2026-08-12T14:25:02.636890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.636890Z digest=sha256:eb80739581c1f802c13a857d6222895e81cbd155ec6be2b597af1d6d1010052d

Observation a3f0da25-b2c9-4fd9-80e9-25340c44409f · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 4

Resolution
verified exact
doi, observed 2026-08-12T14:25:03.075853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T14:25:02.643992Z digest=sha256:a9cfe6813ac476135b4f3e5914aad5234cfc4e9eab1904e8e3271710e6f23111

Reference 5

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no resolver link, observed 2026-08-12T14:25:02.650584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.650584Z digest=sha256:3a8b026bb811f9b3a5b051327ad9e940dc70797e20a5d00fdc0c7e47f2048cf3

Observation 6e179ee2-a264-4085-b614-15cfdf6fbd39 · outbound

This paper cites A Simple and Effective Positional Encoding for Transformers.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering A Simple and Effective Positional Encoding for Transformers

Reference 6

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unresolved
no resolver link, observed 2026-08-12T14:25:02.656219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b52037a5-f5a9-4900-8c95-5df816d23b65 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 7

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unresolved
no resolver link, observed 2026-08-12T14:25:02.662836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.662836Z digest=sha256:448cf03796e942890d3d20d459a6c8b0c6bf50c11e15026ccb0115aad7ccd70a

Observation ba7fe4a9-2564-4457-ab19-8aa9f49ee926 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 8

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unresolved
no resolver link, observed 2026-08-12T14:25:02.669046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.669046Z digest=sha256:bb880beeb3baaef13ccf8d4c80a7aebd061b526328f4b9cd5cd89c1b9db8f28c

Observation 7ecb2ec4-522c-49d4-8e0b-2670af8a73d9 · outbound

This paper cites Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6ee81a59-e6bd-406f-817a-8c5544fa2d56 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 10

Resolution
verified exact
doi, observed 2026-08-12T14:25:03.041475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T14:25:02.679271Z digest=sha256:79a1c5e81b66caf55503b326c4df419b305ccd274f91ab93f4db650c8de296a1

Observation 6dcf3c03-41d8-4085-a89e-910c6ea9048f · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d0a4210e-d3b3-470b-a0e2-a5d264e6c630 · outbound

This paper cites Enhancing Transformer RNNs with Multiple Temporal Perspectives.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Enhancing Transformer RNNs with Multiple Temporal Perspectives

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7a14a559-560d-4318-9b0f-fa97b9fe1b01 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 13

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 7a10802e-044a-4aff-8360-d590da0cca0a · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 14

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unresolved
raw_fallback, observed 2026-08-12T14:25:04.343475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T14:25:02.700482Z digest=sha256:641b74183f549c7eba434ae5db2782cea185c22025f10c4ef730e84bd573790e

Observation a1734fcb-6e6b-4fb1-8e36-27580e3a723b · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 15

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T14:25:02.705382Z digest=sha256:1a7b293f44448c540557e31da8d18f6e979615917dfe68a3b1f45ee8c53e5e39

Observation 70b35772-b912-44d9-a900-730a534a2602 · outbound

This paper cites Sequence Transduction with Recurrent Neural Networks.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Sequence Transduction with Recurrent Neural Networks

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e3ad5091-e783-47db-b7f8-18fa5018387e · outbound

This paper cites Gomez, and J¨urgen Schmidhuber.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Gomez, and J¨urgen Schmidhuber

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation ff6c4bc1-92dd-475b-becd-f977cb7cbf8e · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 18

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unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 4b1da634-d8ce-472c-a22b-87bab9ca3e72 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 19

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation badd3ee9-56b1-40ae-8851-d1e1c3c20f38 · outbound

This paper cites Transformer Language Models without Positional Encodings Still Learn Positional Information.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Transformer Language Models without Positional Encodings Still Learn Positional Information

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2fd16278-7892-43d0-b2e7-d35e93557c6a · outbound

This paper cites Large Language Models for Expansion of Spoken Language Understanding Systems to New Languages.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Large Language Models for Expansion of Spoken Language Understanding Systems to New Languages

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 08b840cc-e689-48c9-a6dd-1d0e4823aff9 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 22

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.743847Z digest=sha256:0d75125ded5d00697c67a77f4e463f10b8097f9db22a56f7899dc99cb32d318c

Observation 06e913af-e016-43c2-973e-22bf1d5250cb · outbound

This paper cites Advancing Transformer Architecture in Long-Context Large Language Models: A Comprehensive Survey.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Advancing Transformer Architecture in Long-Context Large Language Models: A Comprehensive Survey

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 72d5125c-409d-4591-8014-80f55ac07155 · outbound

This paper cites ChunkFormer: Learning Long Time Series with Multi-stage Chunked Transformer.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering ChunkFormer: Learning Long Time Series with Multi-stage Chunked Transformer

Reference 24

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Observation 7f40d93b-31ad-40c3-a77c-a292af47b7f7 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 25

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 117f8556-d1de-4a90-a05b-d20412983936 · outbound

This paper cites BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5c5d4859-2a1c-4024-8cff-2570f840b559 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 27

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Unavailable: canonical work link unavailable.

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Observation 4ba42b1e-8988-49aa-a7ca-8bdaf4c42b00 · outbound

This paper cites Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3e86a310-ce62-4962-95cc-b5f0cce17fd4 · outbound

This paper cites Multilingual Denoising Pre-training for Neural Machine Translation.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Multilingual Denoising Pre-training for Neural Machine Translation

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7737f6ff-6952-49a5-ab40-f31e6e58c51b · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 22b9c92f-8b45-4ead-b04c-d867969c3130 · outbound

This paper cites Effective Approaches to Attention-based Neural Machine Translation.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Effective Approaches to Attention-based Neural Machine Translation

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9737f12d-5602-4cbd-9020-157922f234ff · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 57459e20-6609-40bf-88ef-7155df84d349 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9cc6fa0e-f4aa-41d4-bc9f-e371d852aed7 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 35

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unresolved
raw_fallback, observed 2026-08-12T14:25:04.210151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation bc837e74-ac52-47d0-89c9-8b146056ea37 · outbound

This paper cites Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-12T14:25:02.824727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.824727Z digest=sha256:7f79c3ca3289264b629d799cd1f2ae416c4c41d75a6283cf52f4368b3e7fa73e

Observation e069d320-b1d7-4e75-8b8f-e2c518b09387 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 37

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unresolved
no resolver link, observed 2026-08-12T14:25:02.830010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T14:25:02.835452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.835452Z digest=sha256:3afe219dcfcc6de936e4bbaaaaf9111cd6fa2d356e84e9746bc17dc8c241b103

Observation a80a5e92-0dd8-4ac4-a10c-dbfeb3bdf154 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T14:25:02.841594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.841594Z digest=sha256:4c3940d1cf92de46e09d7fdc825a13969b65f5e3df7377fc7ffd1cba07270e06

Observation e9137352-0eef-4352-89ca-188daa8bef66 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-12T14:25:02.847070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.847070Z digest=sha256:2e80482f3bbfa1e93b2c5c990b9d27fd428071ff6dca6ab8526d5b813d2df06a

Observation 80d490af-f05c-4fa6-973c-82be98097fb1 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:25:04.162159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T14:25:02.852709Z digest=sha256:261d7a80e42077bce16de0fbb4aada991406c5cceb568e703cbac4c3078b92f8

Observation 53c87907-6c67-45ec-8695-a11c094de8e1 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-12T14:25:02.858541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.858541Z digest=sha256:e95c126b2d634c8bd009f33aabb336c75adddebe3d4a4ce9856f85f47e6c2e0d

Observation 15c66090-889f-4f71-aa48-9540c40dd0c5 · outbound

This paper cites Lite Transformer with Long-Short Range Attention.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Lite Transformer with Long-Short Range Attention

Reference 43

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unresolved
no resolver link, observed 2026-08-12T14:25:02.864324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.864324Z digest=sha256:582d8155af1d623b16a25e6eb56a20081a74c8965787803c55e9a56277e198ce

Observation f7e0b12a-ccdc-4df8-b62b-571e68c4542d · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-12T14:25:02.869699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.869699Z digest=sha256:f5505b920f16a3280773d2b9be378b21a69a5f70a1c7aadde7c21475088e0618

Observation 50ca511a-7344-4c1c-9f7b-91f4654ffccb · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:25:04.143731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T14:25:02.875601Z digest=sha256:68c9cf8c427081d09b704d68ea3d7fad42e4beafa936ae00d9a2957ea2b51183

Observation 37db7a2c-185d-4e52-bcf5-41c1c8a3b740 · outbound

This paper cites an unresolved cited work.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Unresolved cited work

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-12T14:25:02.881836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.881836Z digest=sha256:ef2e03cb647460ddf27e77861cde4e65ba9e0df7120bc779def763e0c311ccb9

Reference 47

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unresolved
no resolver link, observed 2026-08-12T14:25:02.887401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.887401Z digest=sha256:021182e40de99a2c6c0943a78d6535263dca55f2f77f7e144b031aa5f7753db2

Observation ce2586a6-7d1e-47f1-839e-60f0d5b3730a · outbound

This paper cites Are Transformers Effective for Time Series Forecasting?.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering Are Transformers Effective for Time Series Forecasting?

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-12T14:25:02.892730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.892730Z digest=sha256:90bcf140c6a8407e659f3a850e8be6af850260840942b2e72f501f4d29a52714

Observation af233a03-a908-4e5e-b9ea-b08c12ff6f90 · outbound

This paper cites URL: " 'urlintro :=.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering URL: " 'urlintro :=

Reference 49

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unresolved
no resolver link, observed 2026-08-12T14:25:02.899281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.899281Z digest=sha256:ccca94ae99e87270277efed3a3d023477f833f7f978ee1a1164351eabb85f9f2

Observation d13b50fe-877c-4a76-a79f-48a961f6c547 · outbound

This paper cites write newline.

Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering write newline

Reference 50

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unresolved
no resolver link, observed 2026-08-12T14:25:02.905354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:25:02.905354Z digest=sha256:126ac3a0a11e2a0235c65502292259ed68a0fceee40c7d00fb0fb81f4e86fcaf

Pith citing papers

No inbound Pith citation observations are available.