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Paper Citation Record · LEDGER

Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2104.06967.

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

pith.paper-citation-record.v1
2104.06967 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:25:12.204362Z

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

4
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 edcfa207-9978-477e-8a17-d4f179dd4f2f · inbound

Unsupervised Dense Information Retrieval with Contrastive Learning cites this paper.

Unsupervised Dense Information Retrieval with Contrastive Learning Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Reference 136

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T13:21:17.139703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-12T13:21:16.921001Z digest=sha256:6701d47fed9baae17b5345da3ea4c6a36183ae0622415172839fc9cfb3c70af6

Observation e230ca38-a544-4fc1-80e8-3da9d36b0282 · inbound

Text and Code Embeddings by Contrastive Pre-Training cites this paper.

Text and Code Embeddings by Contrastive Pre-Training Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T19:24:11.975537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T19:24:11.907204Z digest=sha256:608fdc666f2b5e33ae190327bf06822a8a11871a5d865077f0ab2fd2b7af993a

Observation 0a203ebe-3817-4a42-bf93-cd18511b2d68 · inbound

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

Atlas: Few-shot Learning with Retrieval Augmented Language Models Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Reference 136

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T13:48:43.367037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-16T13:48:43.024120Z digest=sha256:4859747fd056f4be3cd257246ffb38fe3ea80f4e91fb4667d92bb1e58e784467

Observation 428588c0-dd37-490d-a136-58d5d656adca · inbound

O1 Embedder: Let Retrievers Think Before Action cites this paper.

O1 Embedder: Let Retrievers Think Before Action Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-08T12:25:12.204362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:25:12.204362Z digest=sha256:9282bec8ade6e66bd8e21eaf12ae41fbca6b676f52c6e7c0a41d699857de5ed1

Observation aa997e6e-9cfa-45ac-b63c-b6078131a040 · inbound

Statistical Foundations of DIME: Risk Estimation for Practical Index Selection cites this paper.

Statistical Foundations of DIME: Risk Estimation for Practical Index Selection Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-16T15:51:05.219334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T15:50:25.654519Z digest=sha256:9d5c6b7822eac9f5d461e155edbaf5320ccfa8cbeadcb8b0fe4313ff572792db

Observation 0f013acd-9eb4-45a6-9e12-c7ff0d20ebc2 · inbound

Scaling Laws for Cross-Encoder Reranking cites this paper.

Scaling Laws for Cross-Encoder Reranking Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-15T16:10:09.243777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T16:09:58.328527Z digest=sha256:51cf879b328c266d33c175ffb6b0f20adbd4cfe495b4d1308c23a25d446e6a6a

Observation 0d6c2d02-4b0b-404b-b145-9b123b1cfa43 · inbound

VerifAI: A Verifiable Open-Source Search Engine for Biomedical Question Answering cites this paper.

VerifAI: A Verifiable Open-Source Search Engine for Biomedical Question Answering Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-16T14:07:58.471040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T14:03:58.706599Z digest=sha256:b777dc2b5ea57179ef160f14cf14aa9d5992db46f2d8de09eb0f7c79c2c518bc

Observation 5a75f27d-be2d-43eb-b0bd-d69dab62a0d6 · inbound

Certified Domain Consistency for Multi-Domain Retrieval: Label-Free Per-Domain Contamination Control with Conformal Risk Guarantees cites this paper.

Certified Domain Consistency for Multi-Domain Retrieval: Label-Free Per-Domain Contamination Control with Conformal Risk Guarantees Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-02T05:55:31.165725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:55:31.165725Z digest=sha256:166cb4a68a7ad174ffac05b6381289f1d2db591e8bdbd94512084e112ecd7164