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Paper Citation Record · LEDGER

Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2110.06918.

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

pith.paper-citation-record.v1
2110.06918 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:12:37.717840Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a084afee-d14b-41fa-8633-ce13521c3043 · inbound

Unsupervised Dense Information Retrieval with Contrastive Learning cites this paper.

Unsupervised Dense Information Retrieval with Contrastive Learning Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T13:21:17.021988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-12T13:21:16.921001Z digest=sha256:5ada9b8baf45fcffa1cdbe0627794caf7e7cc946823c40171f2b1ffdfcca0a91

Observation 701bb839-656c-46fa-a234-24723c378fae · inbound

Unsupervised Dense Information Retrieval with Contrastive Learning cites this paper.

Unsupervised Dense Information Retrieval with Contrastive Learning Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?

Reference 123

Resolution
verified exact
arxiv_id, observed 2026-05-12T13:21:17.049930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-12T13:21:16.921001Z digest=sha256:1b05a00791a3718034a405a60a26b90535ba125797756c182c07ef4d2048431c

Observation bde6865f-5762-40df-a57d-187530d04907 · inbound

Text Embeddings by Weakly-Supervised Contrastive Pre-training cites this paper.

Text Embeddings by Weakly-Supervised Contrastive Pre-training Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:54:04.013760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-11T04:54:03.524365Z digest=sha256:e8c88665a6d31ea6e8350fdc5783fc31cccdd72746aa0c59ae4532e125fac1b9

Observation 31a8f1db-d9eb-4678-83eb-b5004bebd28b · inbound

Remining Hard Negatives for Generative Pseudo Labeled Domain Adaptation cites this paper.

Remining Hard Negatives for Generative Pseudo Labeled Domain Adaptation Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T15:12:37.717840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:12:37.717840Z digest=sha256:3babf0951064b6fcab17da5ed84031b020e0d02577335590f9cacf9a409de198

Observation f23f4264-86c1-4fd2-b3f0-7d804bb8d2ed · inbound

CG-RAG: Research Question Answering by Citation Graph Retrieval-Augmented LLMs cites this paper.

CG-RAG: Research Question Answering by Citation Graph Retrieval-Augmented LLMs Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T14:46:06.929799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:46:06.929799Z digest=sha256:359251689244644ab8bf1fefbac1f0cce29e252df2ef7524a58096ad0f2c9339