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Paper Citation Record · LEDGER

Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2405.05374.

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

pith.paper-citation-record.v1
2405.05374 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T18:32:13.999106Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T11:38:05.023995Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
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  • 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 85fbbfcf-ab08-43ce-aace-f9f451402e1e · inbound

The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale cites this paper.

The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-13T04:36:45.542534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T04:36:45.363131Z digest=sha256:a3eac0de24be06d4d24ebc7f140aa2abd6f026cc79f2e223f83ae06a67486d9f

Observation 1757fed4-5944-4082-88eb-fdb21d9f29ed · inbound

Agentic Verification for Ambiguous Query Disambiguation cites this paper.

Agentic Verification for Ambiguous Query Disambiguation Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T18:32:13.999106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T18:32:13.999106Z digest=sha256:13a18931d2b4e973f8b9406c28287df0bbdf2482e21833a24b320be92c61a95c

Observation 197d4932-116e-4cd9-ad58-bcfe1b1f7253 · inbound

Conventional Contrastive Learning Often Falls Short: Improving Dense Retrieval with Cross-Encoder Listwise Distillation and Synthetic Data cites this paper.

Conventional Contrastive Learning Often Falls Short: Improving Dense Retrieval with Cross-Encoder Listwise Distillation and Synthetic Data Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T14:23:40.452865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:23:40.452865Z digest=sha256:c893d147e016ffa2b8c113f5ba029981a50c727c15a7beea381ccae7c4c9dbeb

Observation fbe7c7be-26ce-4066-830b-49b528c35c4b · inbound

MedGen: Unlocking Medical Video Generation by Scaling Granularly-annotated Medical Videos cites this paper.

MedGen: Unlocking Medical Video Generation by Scaling Granularly-annotated Medical Videos Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T19:25:08.561628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:25:08.561628Z digest=sha256:8b56671a655f82fe079ef68fc2a9d34ce52b3786202e0f2f1ee1f4586b059c1e

Observation 654212c9-bed7-43c0-900a-fd55476b6aac · inbound

FlexOlmo: Open Language Models for Flexible Data Use cites this paper.

FlexOlmo: Open Language Models for Flexible Data Use Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 112

Resolution
unresolved
no resolver link, observed 2026-08-06T18:57:16.337903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:57:16.337903Z digest=sha256:6c1658517e6128afca022ccb9f678bacd3bddbf9bacbac74fdb711ad430741b2

Observation e6422f96-9a76-42c9-a333-412515d44f18 · inbound

Exploiting Leaderboards for Large-Scale Distribution of Malicious Models cites this paper.

Exploiting Leaderboards for Large-Scale Distribution of Malicious Models Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T18:16:12.707493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:16:12.707493Z digest=sha256:551f1899803c92411352b6d7e1301ec6b9418a6ce8dc85d28346f6ad0388de20

Observation 25ab451c-48e0-473d-b052-c177c268a35e · inbound

Arctic Inference with Shift Parallelism: Fast and Efficient Open Source Inference System for Enterprise AI cites this paper.

Arctic Inference with Shift Parallelism: Fast and Efficient Open Source Inference System for Enterprise AI Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T17:07:49.956821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:07:49.956821Z digest=sha256:292b7d25f4e3043c4171e090eba061f440b17fdf93d094193ad1591f2b707e0a

Observation 84bbaabe-9546-4bca-8463-bf6be57a6fd4 · inbound

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection cites this paper.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T15:49:00.035067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:49:00.035067Z digest=sha256:dc1679d2ab88ca89f691cbdb81773b950a5b21a487becaed81086c585bb99275

Observation e849a026-4515-4d73-88bb-bd7e19e01fd5 · inbound

Boosting Data Utilization for Multilingual Dense Retrieval cites this paper.

Boosting Data Utilization for Multilingual Dense Retrieval Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-04T19:07:21.369020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:07:21.369020Z digest=sha256:3af36632ff1b761fe824907c4b9c36bcaf0d747cd0dcbbbd7c373ca2f344e3cf

Observation 409ce440-25a0-489c-9e64-73c720b8a0c8 · inbound

LEAF: Knowledge Distillation of Text Embedding Models with Teacher-Aligned Representations cites this paper.

LEAF: Knowledge Distillation of Text Embedding Models with Teacher-Aligned Representations Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-18T17:16:40.196782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T17:13:10.779903Z digest=sha256:8cba2367fb8fa386455b293dbba3e36ad57a1b269f781335d618c7d47a749964

Observation c67621af-dfe5-45fb-938b-2407d5a6dbaf · inbound

Removing Noise, not Finding Gold: Quality Filtering for Large-Scale Pretraining cites this paper.

Removing Noise, not Finding Gold: Quality Filtering for Large-Scale Pretraining Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-04T13:24:15.511639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:24:15.511639Z digest=sha256:b635010c4e8d4ee7bec357d479d1bf486bd180131df0af9e4d2fd930bf1478e0

Observation 5ad4defc-bd6f-4909-bd0d-ebc5976ed605 · inbound

SkillRet: A Large-Scale Benchmark for Skill Retrieval in LLM Agents cites this paper.

SkillRet: A Large-Scale Benchmark for Skill Retrieval in LLM Agents Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:36:07.996356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T11:39:06.544414Z digest=sha256:554f7c60ba922d864a9a3db0d5187b217f4bd7126ddd780a870a67eb94c4e834

Observation e1be5f40-285a-49f0-a543-b24baa22ae19 · inbound

Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs cites this paper.

Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-14T21:58:04.037404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-14T21:50:10.564922Z digest=sha256:6baddf4160fcb5b88f102e4ac7634fa0942887f39ace4b5cb1774be01d31029e

Observation 91e8a115-983a-41f9-b7c3-f50527c01b90 · inbound

MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration cites this paper.

MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-06-30T12:34:38.808985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T12:27:46.629948Z digest=sha256:fa4e2bcde01bf8fdec8a1c726123591870ab75a39301b4eabe32fafe16b1834a

Observation 770392d8-81e8-4883-b9dc-6010e2ab6ada · inbound

On the Robustness of Multilingual Text Embedding Rankings Across Learning Tasks, Languages, and Benchmark Datasets cites this paper.

On the Robustness of Multilingual Text Embedding Rankings Across Learning Tasks, Languages, and Benchmark Datasets Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-01T19:26:00.244397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T22:43:27.232092Z digest=sha256:8775a612c1489dbe39699cb8c16e64c8cb7da2be2367b6fe27660d5042832183

Observation b5e59e42-1491-4e95-bf85-877208550d44 · inbound

Measuring Semantic Progress in Multi-turn Dialogue via Information Gain cites this paper.

Measuring Semantic Progress in Multi-turn Dialogue via Information Gain Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-07-03T11:38:05.025609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T09:28:11.355553Z digest=sha256:4bac0c17d0646d339ae0d8e164cf9df6368537a3908e193c7d3183aaf484f1b7

Observation 8306f99a-2e4a-47ba-9cec-5bca3c7661f1 · inbound

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval cites this paper.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-02T05:38:04.815422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:04.815422Z digest=sha256:ba068e317950daae14043259e515c8ce17d787db70b112e11690f81ef9b777e5

Observation cc4fddef-3fe8-4548-a187-72516c96b027 · inbound

DenseOn with the LateOn: Fully Open Dense and Late-Interaction Models for Multilingual, Long-Context, and Code Search cites this paper.

DenseOn with the LateOn: Fully Open Dense and Late-Interaction Models for Multilingual, Long-Context, and Code Search Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 126

Resolution
unresolved
no resolver link, observed 2026-07-30T11:17:16.864177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T11:17:16.864177Z digest=sha256:d849e8e465397b1340229e87fd3ae3bdc74a071326aa998e5d375c159b1f872f

Observation 91a371ec-e787-4899-bfce-857d69bec5ba · inbound

DenseOn with the LateOn: Fully Open Dense and Late-Interaction Models for Multilingual, Long-Context, and Code Search cites this paper.

DenseOn with the LateOn: Fully Open Dense and Late-Interaction Models for Multilingual, Long-Context, and Code Search Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 144

Resolution
unresolved
no resolver link, observed 2026-08-03T01:43:17.325549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T01:43:17.325549Z digest=sha256:5a411f037e353ea52d59d81e21168c8d4313ea7ef0f6ceef0c6fff595b59f910