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Paper Citation Record · LEDGER

Overcoming Non-monotonicity in Transducer-based Streaming Generation

As of 20 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 3 inbound Pith citation observations for arXiv:2411.17170.

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

pith.paper-citation-record.v1
2411.17170 v2

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:33:11.568505Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:30:21.937008Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:37:34.387533Z

Reference resolution

52 of 52 outbound references displayed

  • verified exact11
  • verified fuzzy11
  • unresolved30
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f71676df-3683-4c9d-bf1a-65e65a93c601 · outbound

This paper cites Monotonic infinite lookback attention for simultaneous machine translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Monotonic infinite lookback attention for simultaneous machine translation

Reference 1

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no resolver link, observed 2026-08-12T12:33:11.380918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.380918Z digest=sha256:51eaa9d63a0e11959f660be857bdc995c68122989a6b42da172dbe32a0b9db22

Observation 3c97aff1-9e8c-4810-adce-b1110f3119af · outbound

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

Overcoming Non-monotonicity in Transducer-based Streaming Generation Neural Machine Translation by Jointly Learning to Align and Translate

Reference 3

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no resolver link, observed 2026-08-12T12:33:11.389903Z

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source=arxiv_source observed=2026-08-12T12:33:11.389903Z digest=sha256:b5024658c432dd4d80ed20dcf5367179ca41452a4f1b1e621b9dba5806df2575

Observation d8cfad1c-8ef4-4cc5-9ddb-7334d80c4b16 · outbound

This paper cites and Raffel, C.

Overcoming Non-monotonicity in Transducer-based Streaming Generation and Raffel, C

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-12T12:33:12.363961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.393703Z digest=sha256:1c6ec64462587462cda7bc80fffa541457f147dcf759d9c30fc19871baeebc5f

Observation 7db7c352-56f9-44b2-9fad-d7da68b08efe · outbound

This paper cites Can neural machine translation do simultaneous translation?.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Can neural machine translation do simultaneous translation?

Reference 5

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no resolver link, observed 2026-08-12T12:33:11.397566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.397566Z digest=sha256:00a0420fa9acff70f931402b58e5e29209c4b375110e231b8f35df326b6181a9

Observation c4c82c89-478e-442e-842e-19046154b7cf · outbound

This paper cites Investigating the reordering capability in CTC -based non-autoregressive end-to-end speech translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Investigating the reordering capability in CTC -based non-autoregressive end-to-end speech translation

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.401522Z digest=sha256:c2df32bf900f24617bbdf1939208b2aed0fe1641d3d2e2413aeed52ee0343ca7

Observation e8c2220a-73dc-46ca-8070-62c97b847008 · outbound

This paper cites A., Cattoni, R., Bentivogli, L., Negri, M., and Turchi, M.

Overcoming Non-monotonicity in Transducer-based Streaming Generation A., Cattoni, R., Bentivogli, L., Negri, M., and Turchi, M

Reference 7

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no resolver link, observed 2026-08-12T12:33:11.405640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.405640Z digest=sha256:327c3f04f2eabb4725939e9f986d353c6c4779789d959cdbd6d2f808035968f5

Observation 1a0794e7-57b4-4542-8f61-f05aceec1e1b · outbound

This paper cites Sequence Transduction with Recurrent Neural Networks.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Sequence Transduction with Recurrent Neural Networks

Reference 8

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no resolver link, observed 2026-08-12T12:33:11.408890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.408890Z digest=sha256:8ede296a75342ab1a96db8284b307b717e7809a78c10345a8ab9c21b7c49f202

Observation 9076acd1-6259-425f-9cbe-3462855496d9 · outbound

This paper cites Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks

Reference 9

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no resolver link, observed 2026-08-12T12:33:11.412371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.412371Z digest=sha256:7ecb7aa2ae7817168911fe43e7d136e5318bc9eeb90ce2510e36eceb7f968126

Observation 7872c97c-61a7-44d9-91c0-bcf977207d34 · outbound

This paper cites an unresolved cited work.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Unresolved cited work

Reference 10

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raw_fallback, observed 2026-08-12T12:33:12.354514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.415585Z digest=sha256:c2cd8e2a996be04e086dd2ee2eb3f379345db197d304c3220866dcac53abd297

Observation ab8d9a2c-ffa0-4ee4-b093-5666ac5d2d31 · outbound

This paper cites Large Language Models Are Read/Write Policy-Makers for Simultaneous Generation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Large Language Models Are Read/Write Policy-Makers for Simultaneous Generation

Reference 11

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source=arxiv_source observed=2026-08-12T12:33:11.418984Z digest=sha256:ae21e37bfc26849ba025bd02d2e05b4231eec80bf2a9fe5a5fa73b9338c785ff

Observation c1b6d357-a2f4-40e2-814e-400904ee9b7d · outbound

This paper cites CVSS corpus and massively multilingual speech-to-speech translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation CVSS corpus and massively multilingual speech-to-speech translation

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-12T12:33:12.344794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.422353Z digest=sha256:d4a09747d8a4a37ec66c74a0d4fac41b630147766b111462b509a2525f387eb7

Observation 8ea2c172-56b7-4df5-afa2-c062dfa5de7a · outbound

This paper cites and Rush, A.

Overcoming Non-monotonicity in Transducer-based Streaming Generation and Rush, A

Reference 13

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no resolver link, observed 2026-08-12T12:33:11.425264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.425264Z digest=sha256:72548c29a0bbaf126194c19914e943d28f9214e2d3b66ef12ee9596a4270782f

Observation 796cf58a-8021-4224-a750-dbefadfa9a0c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Adam: A Method for Stochastic Optimization

Reference 14

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.429153Z digest=sha256:eedd9f6ad523c73936d139ae2ae6c359ac9c06b64cdb82d3bf61bad59be61e8a

Observation 62c28119-edcd-4f45-9000-30b5be68860a · outbound

This paper cites and Richardson, J.

Overcoming Non-monotonicity in Transducer-based Streaming Generation and Richardson, J

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.432791Z digest=sha256:fb824d45a9e908dd85ae62bc57da2ad531e305d86b81563e1f4a0c839c3245ad

Observation 43f13d06-82b2-441f-9842-c1ac581e2d01 · outbound

This paper cites Cross attention augmented transducer networks for simultaneous translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Cross attention augmented transducer networks for simultaneous translation

Reference 16

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no resolver link, observed 2026-08-12T12:33:11.436680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.436680Z digest=sha256:513ebe5e51265be338c26db92ed8b246e69368ad7af1b81d75bd42933643f5e1

Observation 111cc5e1-b033-4654-81cb-9660ae4003c6 · outbound

This paper cites STACL : Simultaneous translation with implicit anticipation and controllable latency using prefix-to-prefix framework.

Overcoming Non-monotonicity in Transducer-based Streaming Generation STACL : Simultaneous translation with implicit anticipation and controllable latency using prefix-to-prefix framework

Reference 17

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no resolver link, observed 2026-08-12T12:33:11.440357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.440357Z digest=sha256:0f46172020e869db77348e7bbd9f878d9fdc7f6355214a1cc3a476858f8fe30b

Observation 0108bd8e-4004-4186-96f0-87fc806616e0 · outbound

This paper cites Incremental text-to-speech synthesis with prefix-to-prefix framework.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Incremental text-to-speech synthesis with prefix-to-prefix framework

Reference 18

Resolution
verified exact
doi, observed 2026-08-12T12:33:11.729877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.443904Z digest=sha256:e3e655b44397768df6753c80b01c8fbf0d5d4e212fcfa7235615c19c74e0af5c

Observation 5fbe7d0b-fab1-4dee-8ba6-c2dbe66904ea · outbound

This paper cites J., Wang, C., Gu, J., and Pino, J.

Overcoming Non-monotonicity in Transducer-based Streaming Generation J., Wang, C., Gu, J., and Pino, J

Reference 19

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verified exact
doi, observed 2026-08-12T12:33:11.719193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.447840Z digest=sha256:a3ef32ab78161bf4208a34259af2299b7a2b033691e882b6ae6458262f4478a5

Observation a8540e25-f18c-4081-834e-a3c49e9d8767 · outbound

This paper cites S imul MT to S imul ST : Adapting simultaneous text translation to end-to-end simultaneous speech translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation S imul MT to S imul ST : Adapting simultaneous text translation to end-to-end simultaneous speech translation

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-12T12:33:12.334586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.451490Z digest=sha256:8dd7fc055179b8a790ac4ffcdbef9a00f5fefbbc3d5239f61fa113305687869e

Observation aea8aa67-7572-4121-9974-242b408f21e2 · outbound

This paper cites M., Cross, J., Puzon, L., and Gu, J.

Overcoming Non-monotonicity in Transducer-based Streaming Generation M., Cross, J., Puzon, L., and Gu, J

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-12T12:33:12.323948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.455058Z digest=sha256:403d53b1dd9d4d320e9ca611f8143af3659bc904da0b3870c29657d6aafbdaae

Observation 39df17a2-ee3b-4def-9e99-e6f9860a68d2 · outbound

This paper cites Direct simultaneous speech-to-speech translation with variational monotonic multihead attention, 2022.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Direct simultaneous speech-to-speech translation with variational monotonic multihead attention, 2022

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-12T12:33:12.312738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.458622Z digest=sha256:3b17e78328d16a375bc1f59648cdf8c289b27a7bb60c73ea601429cc2cd31310

Observation 2c03531b-ae81-48ae-b28d-18767498a24a · outbound

This paper cites Efficient Monotonic Multihead Attention.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Efficient Monotonic Multihead Attention

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.462179Z digest=sha256:5f8a041b2ca8d8865580756eb204f80b1e4b91277bfcc7d91769e3b1c5c01063

Observation e74eb34c-ebff-4f9d-9fe8-c24b935d3a3c · outbound

This paper cites Fuzzy Alignments in Directed Acyclic Graph for Non-Autoregressive Machine Translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Fuzzy Alignments in Directed Acyclic Graph for Non-Autoregressive Machine Translation

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-12T12:33:12.071551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.465998Z digest=sha256:3e2db94f05a2d5f3382e1cb6fe247a8af61c10821c461a623e04d825179861e9

Observation d97a7c4f-c677-4911-845d-20b5ef6f348c · outbound

This paper cites Non-autoregressive streaming transformer for simultaneous translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Non-autoregressive streaming transformer for simultaneous translation

Reference 25

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verified exact
doi, observed 2026-08-12T12:33:11.708981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.469701Z digest=sha256:06ff669fca13682a59f0b70a88f168b75d3c4141fd878abb2e1cc2e341047f58

Observation 693c32c7-0d6a-4842-8983-26b0d5c31ded · outbound

This paper cites A non-autoregressive generation framework for end-to-end simultaneous speech-to-any translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation A non-autoregressive generation framework for end-to-end simultaneous speech-to-any translation

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-12T12:33:12.302062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.473483Z digest=sha256:05b6cd3b3c1b6fd1b34d197780735c274fd6656a59d9945aeb7e46a707f3d933

Observation 5f2dfad7-4158-4b5e-b954-91b887a585ac · outbound

This paper cites Montreal forced aligner: Trainable text-speech alignment using kaldi.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Montreal forced aligner: Trainable text-speech alignment using kaldi

Reference 27

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no resolver link, observed 2026-08-12T12:33:11.477845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.477845Z digest=sha256:265ef9108c05fc19fd0a1343541fe8b7fb84ca14bcd0a26f1d7962ff7c8ac8c1

Observation a641bcd1-f6c4-45f8-b1aa-c57fb8e46a03 · outbound

This paper cites Over-generation cannot be rewarded: Length-adaptive average lagging for simultaneous speech translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Over-generation cannot be rewarded: Length-adaptive average lagging for simultaneous speech translation

Reference 28

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no resolver link, observed 2026-08-12T12:33:11.481471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.481471Z digest=sha256:84ff0135ebd468ceddb5568d6428e913dcd6761ec916b042bdd4b735bcbf7dc6

Observation 994f99d0-6815-4ce5-89c2-b4b07e68fefe · outbound

This paper cites Attention as a guide for simultaneous speech translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Attention as a guide for simultaneous speech translation

Reference 29

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no resolver link, observed 2026-08-12T12:33:11.485081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.485081Z digest=sha256:3cebab4c6e069efebdb4d5acfcecdc84a76876d375c756ef132437ebdc8f4064

Observation c81c7395-9df9-44b1-8a71-93f4daf74c48 · outbound

This paper cites AlignAtt: Using Attention-based Audio-Translation Alignments as a Guide for Simultaneous Speech Translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation AlignAtt: Using Attention-based Audio-Translation Alignments as a Guide for Simultaneous Speech Translation

Reference 30

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no resolver link, observed 2026-08-12T12:33:11.488690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.488690Z digest=sha256:30017584e74d2e2c0c4acb5fdad8d78652644822044976841fa76fad9b74cba3

Observation 1e75213c-37cf-4961-8ada-6bbcf9d5817d · outbound

This paper cites B leu: a method for automatic evaluation of machine translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation B leu: a method for automatic evaluation of machine translation

Reference 31

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unresolved
no resolver link, observed 2026-08-12T12:33:11.492369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.492369Z digest=sha256:1a56a909f05d7cc64742a026b5488e07297fa65e07365d4279a054cfe9a7ec6d

Observation 05b43924-3be6-4e90-ba57-80fa8fd5960a · outbound

This paper cites S., Chan, W., Zhang, Y., Chiu, C.-C., Zoph, B., Cubuk, E.

Overcoming Non-monotonicity in Transducer-based Streaming Generation S., Chan, W., Zhang, Y., Chiu, C.-C., Zoph, B., Cubuk, E

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:33:12.290524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.495816Z digest=sha256:73a257a5974fc8952452a62ff8b3dc86fab4d64ced9bbe705c9e7084cefad01d

Observation 43549234-d0a2-4699-8eb3-b3b9a818c15c · outbound

This paper cites A call for clarity in reporting BLEU scores.

Overcoming Non-monotonicity in Transducer-based Streaming Generation A call for clarity in reporting BLEU scores

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:33:12.277949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.499393Z digest=sha256:1d958f28bb0949228b244bf1decd849ee9c56b1a08e299c4b2be36f6ffafe6be

Observation 5d2ac85e-6509-4969-a3b6-03e9f3d965ff · outbound

This paper cites N., Li, B., Johnson, L., and Jaitly, N.

Overcoming Non-monotonicity in Transducer-based Streaming Generation N., Li, B., Johnson, L., and Jaitly, N

Reference 34

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verified exact
doi, observed 2026-08-12T12:33:11.672193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.502719Z digest=sha256:8189c42c10a46984e4c0ff4d5f3e520e76dd30e989b68bbb673cde6447e1a527

Observation f7a6c693-7b0a-402f-8f3f-6b1524131113 · outbound

This paper cites J., Weiss, R.

Overcoming Non-monotonicity in Transducer-based Streaming Generation J., Weiss, R

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-12T12:33:12.265853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.506139Z digest=sha256:ba3ddfeab732cb1ed0a0b1db25ac63b6aa208ca77e79532e327f94207180c2c2

Observation 32352827-149d-4e53-b5b1-5b5130d75034 · outbound

This paper cites an unresolved cited work.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Unresolved cited work

Reference 36

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unresolved
raw_fallback, observed 2026-08-12T12:33:12.254368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.508996Z digest=sha256:30973278e27a3e43d9238583e42f8b5165b4dd3560dac4a1470752573baa25dd

Observation 8bde95bc-1816-4aca-9bc1-6b955fbc5182 · outbound

This paper cites Speech ReaLLM -- Real-time Streaming Speech Recognition with Multimodal LLMs by Teaching the Flow of Time.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Speech ReaLLM -- Real-time Streaming Speech Recognition with Multimodal LLMs by Teaching the Flow of Time

Reference 37

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no resolver link, observed 2026-08-12T12:33:11.512099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.512099Z digest=sha256:d163712eb2a43286112235765322cb558b757506ad2dda7933cc210e0668e61e

Observation 96aae996-d714-4929-950d-433c01784b0f · outbound

This paper cites Non-Monotonic Latent Alignments for CTC-Based Non-Autoregressive Machine Translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Non-Monotonic Latent Alignments for CTC-Based Non-Autoregressive Machine Translation

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-12T12:33:11.963728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.515080Z digest=sha256:ced32611e6f2a5eb65f42d285cdcbded46b6f298d2fde6cba4dd12db902cf157

Observation 4f3f0340-5aa3-49aa-a749-bcaba520b0df · outbound

This paper cites Self-attention with relative position representations.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Self-attention with relative position representations

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T12:33:11.518184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.518184Z digest=sha256:4b5056aa0965bb4c6fc4bb9f8547b08b60bba09934505405f5f9792f57bc399a

Observation 38f97121-bb08-4ea2-8213-cdd314ffdd7f · outbound

This paper cites Emformer: Efficient memory transformer based acoustic model for low latency streaming speech recognition.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Emformer: Efficient memory transformer based acoustic model for low latency streaming speech recognition

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-12T12:33:11.521236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.521236Z digest=sha256:02794be7dc8eb621bcd7d9bb3f8c47c2515e66a5b78349678c84a0bc6f3e0633

Observation 57f04797-85ae-4bd1-adff-bea0230cd881 · outbound

This paper cites Hybrid transducer and attention based encoder-decoder modeling for speech-to-text tasks.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Hybrid transducer and attention based encoder-decoder modeling for speech-to-text tasks

Reference 41

Resolution
verified exact
doi, observed 2026-08-12T12:33:11.653754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.524055Z digest=sha256:ddf449bb16b9c1bfe58671c027fa3d28a5f9b90441b682e8c76a52b39c420504

Observation 2ec9a1c2-8bd4-4044-bb3e-3d3ff8cbdd1d · outbound

This paper cites Attention Is All You Need.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Attention Is All You Need

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-12T12:33:11.527575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.527575Z digest=sha256:4d8c881b3477b3f6b222ff462a06c7b44790d7618700aa44671e885eb0a2c567

Observation 4016ff18-2ec7-4869-b661-78fb70ab7ae0 · outbound

This paper cites LAMASSU: A Streaming Language-Agnostic Multilingual Speech Recognition and Translation Model Using Neural Transducers.

Overcoming Non-monotonicity in Transducer-based Streaming Generation LAMASSU: A Streaming Language-Agnostic Multilingual Speech Recognition and Translation Model Using Neural Transducers

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T12:33:11.531562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.531562Z digest=sha256:3634ce458cd015274bec801786d0c45569ae8ec952f5ada4e22eb9cbec7e1a41

Observation f2f3c9a2-6f4f-4f8a-b831-a313fb21c94a · outbound

This paper cites S tream V oice: Streamable context-aware language modeling for real-time zero-shot voice conversion.

Overcoming Non-monotonicity in Transducer-based Streaming Generation S tream V oice: Streamable context-aware language modeling for real-time zero-shot voice conversion

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:33:12.244031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.535057Z digest=sha256:684d5a9a43098da1b4d19fd97a0b4c16b9ffa82bb19638a58b693f4262ff7ac8

Observation bf21fd74-d954-4ba5-a851-be9e59cf5159 · outbound

This paper cites Streaming Transformer-Based Acoustic Models Using Self-Attention with Augmented Memory.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Streaming Transformer-Based Acoustic Models Using Self-Attention with Augmented Memory

Reference 45

Resolution
verified exact
doi, observed 2026-08-12T12:33:11.636060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.538465Z digest=sha256:754314650d5407c8b06e56a0c5992d44b3b5e5c44e1b89d9bede7a06859bb5e8

Observation 20b5c440-8c72-4254-b69d-e85f8aa714ba · outbound

This paper cites Large-Scale Streaming End-to-End Speech Translation with Neural Transducers.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Large-Scale Streaming End-to-End Speech Translation with Neural Transducers

Reference 46

Resolution
verified exact
doi, observed 2026-08-12T12:33:11.624618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.542118Z digest=sha256:367e1287207ae8570823a88610a1ec0fac27229fd103a9c18cabbfa75832fc75

Observation f0cc9c84-c17f-41a6-93fa-8a9e0e6d706a · outbound

This paper cites R eal T ran S : End-to-end simultaneous speech translation with convolutional weighted-shrinking transformer.

Overcoming Non-monotonicity in Transducer-based Streaming Generation R eal T ran S : End-to-end simultaneous speech translation with convolutional weighted-shrinking transformer

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-12T12:33:11.545532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.545532Z digest=sha256:2d077a31a3d450293d4659e3bb1da609ebb6720a7156617a4c8e7ad2ff20db12

Observation 4278c33e-1763-41ef-aed1-6b49cdf44476 · outbound

This paper cites Transformer transducer: A streamable speech recognition model with transformer encoders and rnn-t loss.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Transformer transducer: A streamable speech recognition model with transformer encoders and rnn-t loss

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-12T12:33:11.548877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.548877Z digest=sha256:c322430e5f37c9f0062a62260216daed6520f2c1af7071c20148bc19ff9e3453

Observation 53d1f52d-f7c0-45d9-b1b2-43dc516321eb · outbound

This paper cites Learning adaptive segmentation policy for end-to-end simultaneous translation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Learning adaptive segmentation policy for end-to-end simultaneous translation

Reference 49

Resolution
verified exact
doi, observed 2026-08-12T12:33:11.604839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.552567Z digest=sha256:13ddd403ec1f0ecdcc5e24193afbeacf3f74a8f7cc13cd7f13796f0c159cbcfc

Observation b2e137db-6d73-4f82-95df-311eb8175229 · outbound

This paper cites Unified Segment-to-Segment Framework for Simultaneous Sequence Generation.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Unified Segment-to-Segment Framework for Simultaneous Sequence Generation

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-08-12T12:33:11.801446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.556521Z digest=sha256:68db756756cfdcbff39d9d1d4302e0279028c439a349a6a64682b7626fc3cc41

Observation 5d2a53ca-642f-4956-b034-fcaead34160d · outbound

This paper cites Streamspeech: Simultaneous speech-to-speech translation with multi-task learning.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Streamspeech: Simultaneous speech-to-speech translation with multi-task learning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:33:12.233304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-12T12:33:11.560742Z digest=sha256:f6de333eafafbd49460efd83720328269d2513f037d53dda4917334f5bed9687

Observation 930fe76c-f78f-48ea-8c95-f6168f7f2ef2 · outbound

This paper cites Textless Streaming Speech-to-Speech Translation using Semantic Speech Tokens.

Overcoming Non-monotonicity in Transducer-based Streaming Generation Textless Streaming Speech-to-Speech Translation using Semantic Speech Tokens

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-12T12:33:11.564252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.564252Z digest=sha256:a5e0ec7bb176f91778b237cd058ea2f04cdc7c9fd643b6cf2093eeb47768959f

Observation b3926c2f-8cc2-4c67-a985-00cb6b64e5fa · outbound

This paper cites write newline.

Overcoming Non-monotonicity in Transducer-based Streaming Generation write newline

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-12T12:33:11.568505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:33:11.568505Z digest=sha256:2428004637e54b38f5233c7faf75324013f9d0732538568d97b13ff9b464b9a8

Pith citing papers

Observation 2cb61f76-39a3-44a0-b78d-fd4cb513c366 · inbound

Large Language Models Are Read/Write Policy-Makers for Simultaneous Generation cites this paper.

Large Language Models Are Read/Write Policy-Makers for Simultaneous Generation Overcoming Non-monotonicity in Transducer-based Streaming Generation

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-10T22:45:34.118358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:45:34.118358Z digest=sha256:02e7703bedfa8ca3914c54297b364f4ad2d9dc36cd50078efdb58434a6e7216f

Observation e979dbd3-84b2-44fc-a552-5625e57c4a24 · inbound

SimulS2S-LLM: Unlocking Simultaneous Inference of Speech LLMs for Speech-to-Speech Translation cites this paper.

SimulS2S-LLM: Unlocking Simultaneous Inference of Speech LLMs for Speech-to-Speech Translation Overcoming Non-monotonicity in Transducer-based Streaming Generation

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-16T11:30:21.937008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:30:21.937008Z digest=sha256:db142abaff2e741fcc06191d49a9c0dd22edbdcc41c990a5cf6fddfddc03c4a6

Observation c03a78d4-66e7-4381-b709-2bc0ba86d9fe · inbound

StreamUni: Achieving Streaming Speech Translation with a Unified Large Speech-Language Model cites this paper.

StreamUni: Achieving Streaming Speech Translation with a Unified Large Speech-Language Model Overcoming Non-monotonicity in Transducer-based Streaming Generation

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:37:34.392422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-06T18:37:34.165214Z digest=sha256:408eed45b7309b53591f3c48142b22b5c4185dba4cf8efa3c64edb4715846937