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Paper Citation Record · LEDGER

Multi-view Recurrent Neural Acoustic Word Embeddings

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1611.04496.

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

pith.paper-citation-record.v1
1611.04496 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:37:59.117518Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T14:39:58.362376Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation fa634f7b-63f2-4932-b785-2193b467fed3 · inbound

Multimodal and Multi-view Models for Emotion Recognition cites this paper.

Multimodal and Multi-view Models for Emotion Recognition Multi-view Recurrent Neural Acoustic Word Embeddings

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-05-25T17:16:04.475773Z

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.

source=arxiv_source observed=2026-05-25T17:14:41.314868Z digest=sha256:1b19a806c338024a40c2c68b81befd00ffdfd77b121a52d089607c8facdb45da

Observation ca1f2d44-c863-4aed-b244-a6c2dbf5bd33 · inbound

To Tune or Not To Tune? How About the Best of Both Worlds? cites this paper.

To Tune or Not To Tune? How About the Best of Both Worlds? Multi-view Recurrent Neural Acoustic Word Embeddings

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-25T00:46:30.585029Z

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.

source=pdf_text observed=2026-05-25T00:45:10.865484Z digest=sha256:10e8120fd8b186988a082bfa0b51ca1e1aeff0290b8f175c7388d7242b0c48ee

Observation a48f4441-b620-436b-a8f0-0117844de30d · inbound

BEST-STD: Bidirectional Mamba-Enhanced Speech Tokenization for Spoken Term Detection cites this paper.

BEST-STD: Bidirectional Mamba-Enhanced Speech Tokenization for Spoken Term Detection Multi-view Recurrent Neural Acoustic Word Embeddings

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-12T15:37:59.117518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:37:59.117518Z digest=sha256:bd114c699ce7fb97fa02f87898322f4000b6d40f10caa41b3a2e91c828bf48a6

Observation 264c998d-93aa-4fd9-b554-15bd491ec33f · inbound

PairAlign: A Framework for Sequence Tokenization via Self-Alignment with Applications to Audio Tokenization cites this paper.

PairAlign: A Framework for Sequence Tokenization via Self-Alignment with Applications to Audio Tokenization Multi-view Recurrent Neural Acoustic Word Embeddings

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:16:08.543922Z

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.

source=pdf_text observed=2026-05-08T12:25:52.847432Z digest=sha256:5efee4fcc8bfa0296cb148a5c703a5730ccacf6664f051809716756fd4341cd1

Observation 0f52acb8-6159-428b-96dc-2458b509b4f4 · inbound

PairAlign: A Framework for Sequence Tokenization via Self-Alignment with Applications to Audio Tokenization cites this paper.

PairAlign: A Framework for Sequence Tokenization via Self-Alignment with Applications to Audio Tokenization Multi-view Recurrent Neural Acoustic Word Embeddings

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-06-30T23:15:07.786984Z

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.

source=pdf_text observed=2026-06-30T23:14:32.494076Z digest=sha256:1b5d069b9d4f8cedf16d22078d170d58426ef2fe9cd18a5cebebb22b0abb7445

Observation 320b5429-fb01-443a-8cd1-3ba1d6cee760 · inbound

wav2tok 2.0: Scalable Audio Tokenization Maintaining Explicit Pairwise Token Alignment for Efficient Audio Retrieval cites this paper.

wav2tok 2.0: Scalable Audio Tokenization Maintaining Explicit Pairwise Token Alignment for Efficient Audio Retrieval Multi-view Recurrent Neural Acoustic Word Embeddings

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-07-04T14:39:58.363864Z

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.

source=pdf_text observed=2026-06-26T02:49:35.819155Z digest=sha256:bc0e290841049c1820a750985ebb6384be9baabf3f33085ef5b2177b13c28ca1