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Paper Citation Record · LEDGER

DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2006.03659.

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

pith.paper-citation-record.v1
2006.03659 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:55:23.896159Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T21:33:28.553089Z

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 3091aabf-567d-488b-876e-555b96ee60cc · inbound

Unsupervised Dense Information Retrieval with Contrastive Learning cites this paper.

Unsupervised Dense Information Retrieval with Contrastive Learning DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations

Reference 133

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T13:21:17.119008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-12T13:21:16.921001Z digest=sha256:c3ead4796d1c66d5bd6b857ed7c024085b6c20d3fd34f636f258ffc180a279f5

Observation d1fd548c-195e-431d-89c5-d786f5e769d9 · inbound

Atlas: Few-shot Learning with Retrieval Augmented Language Models cites this paper.

Atlas: Few-shot Learning with Retrieval Augmented Language Models DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations

Reference 121

Resolution
verified exact
arxiv_id, observed 2026-05-16T13:48:43.339274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-16T13:48:43.024120Z digest=sha256:9ab5b93931db4d442e4d5a1a3a1320163c44da6fc1ab46181a40e389a2a5a924

Observation 617e44f7-210e-469c-abc4-072bfa6c5d7d · inbound

MegaFake: A Theory-Driven Dataset of Fake News Generated by Large Language Models cites this paper.

MegaFake: A Theory-Driven Dataset of Fake News Generated by Large Language Models DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-23T21:33:28.557932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-23T21:31:27.597981Z digest=sha256:5cb5b4c2285c09afe0fdd852b9825bd00603a901a9ee0dca4bcfa4c787c9551c

Observation 05fe7256-9a55-46a9-ab55-642613ffa089 · inbound

HNCSE: Advancing Sentence Embeddings via Hybrid Contrastive Learning with Hard Negatives cites this paper.

HNCSE: Advancing Sentence Embeddings via Hybrid Contrastive Learning with Hard Negatives DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-12T17:55:23.896159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T17:55:23.896159Z digest=sha256:a0835d6dc6566a146229af079a91064eb285aefda4374bc74f71eb5a0e2b2886

Observation f4255859-0c64-41bd-9e48-7426f8fa5e66 · inbound

Can bidirectional encoder become the ultimate winner for downstream applications of foundation models? cites this paper.

Can bidirectional encoder become the ultimate winner for downstream applications of foundation models? DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-12T11:38:42.775409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:38:42.775409Z digest=sha256:094a9c0a19c676636e6065411a40ba9c0368a03fc471db178356a24b508070cf

Observation 76fb7864-8e56-4316-be8b-21bb2119fd5b · inbound

Language Models for Adult Service Website Text Analysis cites this paper.

Language Models for Adult Service Website Text Analysis DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T17:31:39.309172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:31:39.309172Z digest=sha256:5c08e947d0b27a0d2346a9535c0d3977527c2494b2ff531d9fd69d5b9ad991d8

Observation 003ee041-6dc2-4f1a-9e65-d44c71621cce · inbound

Learning Text Styles: A Study on Transfer, Attribution, and Verification cites this paper.

Learning Text Styles: A Study on Transfer, Attribution, and Verification DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T15:13:23.135863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:13:23.135863Z digest=sha256:a2525a81ed8dd72b0e362197156dbe3d8035c9e56df206b8c21d2a77fe1ece05