Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T00:04:52.715412Z
Paper Citation Record · LEDGER
Understanding the Influence of Synthetic Data for Text Embedders
As of 18 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2509.06184.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
16 of 16 outbound references displayed
- verified exact0
- verified fuzzy9
- unresolved5
- parse uncertain0
- malformed identifier1
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 3c013b52-e702-4b96-aaf3-952f2d155980 · outbound
This paper cites The Llama 3 Herd of Models.
Understanding the Influence of Synthetic Data for Text Embedders The Llama 3 Herd of Models
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T00:04:52.448262Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3bd268d8-1599-488d-bb66-28e8c37eb4d3 · outbound
This paper cites In Proceedings of the 17th Conference of the European Chapter of the Association for Com- putational Linguistics, pages 2014–2037, Dubrovnik, Croatia.
Understanding the Influence of Synthetic Data for Text Embedders In Proceedings of the 17th Conference of the European Chapter of the Association for Com- putational Linguistics, pages 2014–2037, Dubrovnik, Croatia
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:04:52.948889Z
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.
Observation 24e9f938-c13f-4f45-a445-519c60c12da0 · outbound
This paper cites (2022) were among the first to demon- strate that a powerful decoder -only LLM can be transformed into a high -quality text encoder.
Understanding the Influence of Synthetic Data for Text Embedders (2022) were among the first to demon- strate that a powerful decoder -only LLM can be transformed into a high -quality text encoder
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:04:52.910177Z
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.
Observation 62ebadba-ce30-4647-873b-a2b8c5ef91e4 · outbound
This paper cites In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 9414–9423, Singapore.
Understanding the Influence of Synthetic Data for Text Embedders In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 9414–9423, Singapore
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:04:52.923699Z
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.
Observation c1b7da2b-d347-4a06-ad34-2ae46a6fcac7 · outbound
This paper cites Qwen2 Technical Report.
Understanding the Influence of Synthetic Data for Text Embedders Qwen2 Technical Report
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T00:04:52.691547Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14973483-4bde-4f77-aaba-a8b49fa9cbf1 · outbound
This paper cites They per- form parameter-efficient fine-tuning via LoRA (Hu et al., 2022), using a batch size of.
Understanding the Influence of Synthetic Data for Text Embedders They per- form parameter-efficient fine-tuning via LoRA (Hu et al., 2022), using a batch size of
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:04:52.895766Z
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.
Observation 6250ad01-919b-43d7-8fde-f04f3851983b · outbound
This paper cites We use the AdamW optimizer with a learning rate of4e−4, linear learn- ing rate warm-up for the first 100 steps, and weight decay with 0.1 coefficient afterwards.
Understanding the Influence of Synthetic Data for Text Embedders We use the AdamW optimizer with a learning rate of4e−4, linear learn- ing rate warm-up for the first 100 steps, and weight decay with 0.1 coefficient afterwards
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:04:52.869685Z
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.
Observation ff6b14ab-a0dd-4a43-98ff-2b7d8958c4aa · outbound
This paper cites In MTEB, every task is reformulated as an em- bedding task where the only requirement is that the model produces a vector (embedding) for each text input.
Understanding the Influence of Synthetic Data for Text Embedders In MTEB, every task is reformulated as an em- bedding task where the only requirement is that the model produces a vector (embedding) for each text input
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:04:52.856612Z
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.
Observation 18ad5f76-cc3d-4f1d-b7ef-72ea3d1f2745 · outbound
This paper cites query":.
Understanding the Influence of Synthetic Data for Text Embedders query":
Reference 16
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-05T00:04:52.843241Z
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.
Observation 9b45e06d-6b0e-4fb7-9a70-b8de54e2658e · outbound
This paper cites MS MARCO: A Human Generated MAchine Reading COmprehension Dataset.
Understanding the Influence of Synthetic Data for Text Embedders MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T00:04:52.193616Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9dd6ef68-7db8-4465-8513-24720baffa94 · outbound
This paper cites Document Expansion by Query Prediction.
Understanding the Influence of Synthetic Data for Text Embedders Document Expansion by Query Prediction
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T00:04:52.678999Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3c4e061e-088e-477f-aa9c-f4c9daf1d836 · outbound
This paper cites In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769–6781, Online.
Understanding the Influence of Synthetic Data for Text Embedders In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769–6781, Online
Reference 2020
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:04:52.961883Z
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.
Observation 39234977-3e5b-43ad-877c-aefbb028fbd3 · outbound
This paper cites In Findings of the Association for Computational Linguistics: EMNLP 2021 , pages 671–688, Punta Cana, Dominican Republic.
Understanding the Influence of Synthetic Data for Text Embedders In Findings of the Association for Computational Linguistics: EMNLP 2021 , pages 671–688, Punta Cana, Dominican Republic
Reference 2021
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:04:52.936144Z
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.
Observation 7803d286-28ea-4f78-9200-3a8b1e5a2646 · outbound
This paper cites Mistral 7B.
Understanding the Influence of Synthetic Data for Text Embedders Mistral 7B
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T00:04:52.317439Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c47c214a-97c4-487c-98b2-c38fbfff8771 · outbound
This paper cites Little Giants: Synthesizing High-Quality Embedding Data at Scale.
Understanding the Influence of Synthetic Data for Text Embedders Little Giants: Synthesizing High-Quality Embedding Data at Scale
Reference 2024
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-05T00:04:52.814288Z
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.
Observation c4986926-a2fa-4fb3-b087-72917b58e598 · outbound
This paper cites Our training procedure largely follows Wang et al., but we make minor modifications inspired by subsequent work.
Understanding the Influence of Synthetic Data for Text Embedders Our training procedure largely follows Wang et al., but we make minor modifications inspired by subsequent work
Reference 2048
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:04:52.882533Z
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.
Pith citing papers
No inbound Pith citation observations are available.