Paper Citation Record · LEDGER

Separating Representation from Reconstruction Enables Scalable Text Encoders

As of 20 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2607.04011.

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

pith.paper-citation-record.v1
2607.04011 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T22:20:52.422988Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

verified exact2
verified fuzzy0
unresolved39
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ace548c8-16a9-42c0-9245-8188fc7159ff · outbound

This paper cites Training compute-optimal transformer encoder models.

Separating Representation from Reconstruction Enables Scalable Text Encoders Training compute-optimal transformer encoder models

Reference 1

Resolution: verified exact; doi, observed 2026-07-11T22:28:20.496998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 03748d60-f13c-4598-b48c-78191ff8a90e · outbound

This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

Separating Representation from Reconstruction Enables Scalable Text Encoders Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation e81b4826-dc72-4069-a966-c9a4452c0966 · outbound

This paper cites NeoBERT: A Next-Generation BERT.

Separating Representation from Reconstruction Enables Scalable Text Encoders NeoBERT: A Next-Generation BERT

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation c267ec25-95f7-444e-9d2a-9b7912ed6ec3 · outbound

This paper cites Nomic Embed: Training a Reproducible Long Context Text Embedder.

Separating Representation from Reconstruction Enables Scalable Text Encoders Nomic Embed: Training a Reproducible Long Context Text Embedder

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation c93a426c-8097-4e02-bbc0-649ce50e6f05 · outbound

This paper cites an unresolved cited work.

Separating Representation from Reconstruction Enables Scalable Text Encoders Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 7396c3bf-c2a6-4ce3-92bf-9225faedadf9 · outbound

This paper cites Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics , pages=.

Separating Representation from Reconstruction Enables Scalable Text Encoders Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics , pages=

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 3cf1f46a-aac4-47b4-a04c-e97ef02f6780 · outbound

This paper cites Rethinking Patch Dependence for Masked Autoencoders.

Separating Representation from Reconstruction Enables Scalable Text Encoders Rethinking Patch Dependence for Masked Autoencoders

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Unavailable: canonical work link unavailable.

Observation 544ba040-2d98-410e-945d-49933a15a2e2 · outbound

This paper cites Cluster and Predict Latent Patches for Improved Masked Image Modeling.

Separating Representation from Reconstruction Enables Scalable Text Encoders Cluster and Predict Latent Patches for Improved Masked Image Modeling

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 79eeae20-b7f4-4d47-97e6-c518ae867bbf · outbound

This paper cites International conference on machine learning , pages=.

Separating Representation from Reconstruction Enables Scalable Text Encoders International conference on machine learning , pages=

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 6daafff7-c458-4ac8-a447-05af2d25aa18 · outbound

This paper cites Proceedings of the IEEE/CVF international conference on computer vision , pages=.

Separating Representation from Reconstruction Enables Scalable Text Encoders Proceedings of the IEEE/CVF international conference on computer vision , pages=

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 4c28df6a-9739-4792-af68-185d9b0e5f5e · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Separating Representation from Reconstruction Enables Scalable Text Encoders DINOv2: Learning Robust Visual Features without Supervision

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 6379d943-2cca-4af0-98b6-1f3f65add56e · outbound

This paper cites DINOv3.

Separating Representation from Reconstruction Enables Scalable Text Encoders DINOv3

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation f3499700-1d26-4260-896f-19330642bd36 · outbound

This paper cites Unsupervised Dense Information Retrieval with Contrastive Learning.

Separating Representation from Reconstruction Enables Scalable Text Encoders Unsupervised Dense Information Retrieval with Contrastive Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 53857998-f47c-40b9-bfa8-8b1c804b38c0 · outbound

This paper cites RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder.

Separating Representation from Reconstruction Enables Scalable Text Encoders RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 69b00ae8-84c5-4040-831f-bce93611320b · outbound

This paper cites Proceedings of the 2018 EMNLP workshop BlackboxNLP: Analyzing and interpreting neural networks for NLP , pages=.

Separating Representation from Reconstruction Enables Scalable Text Encoders Proceedings of the 2018 EMNLP workshop BlackboxNLP: Analyzing and interpreting neural networks for NLP , pages=

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Unavailable: canonical work link unavailable.

Observation 147c304b-e940-4abe-ba3c-dd86b45ca0da · outbound

This paper cites MS MARCO: A Human Generated MAchine Reading COmprehension Dataset.

Separating Representation from Reconstruction Enables Scalable Text Encoders MS MARCO: A Human Generated MAchine Reading COmprehension Dataset

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Unavailable: canonical work link unavailable.

Observation 6081b905-7ad9-451e-bd7c-9665cf5fb463 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Separating Representation from Reconstruction Enables Scalable Text Encoders Advances in Neural Information Processing Systems , volume=

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 08f24245-a9a4-4b5a-a830-758de003b8ff · outbound

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

Separating Representation from Reconstruction Enables Scalable Text Encoders Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation f5754cf5-b3f6-45bd-b967-f5a772023d9d · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

Separating Representation from Reconstruction Enables Scalable Text Encoders Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e6e4f8f-f1c6-4382-84b7-51b23a71b3e7 · outbound

This paper cites VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning.

Separating Representation from Reconstruction Enables Scalable Text Encoders VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2574f0cd-bd8d-4b30-aaf4-6750e568f37e · outbound

This paper cites Learning and Leveraging World Models in Visual Representation Learning.

Separating Representation from Reconstruction Enables Scalable Text Encoders Learning and Leveraging World Models in Visual Representation Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16367a4d-aa9b-49df-a479-003bd4bd73bb · outbound

This paper cites LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics.

Separating Representation from Reconstruction Enables Scalable Text Encoders LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Unavailable: canonical work link unavailable.

Observation 44839e14-19b5-4577-a689-1ea2025bf5ff · outbound

This paper cites Perception Encoder: The best visual embeddings are not at the output of the network.

Separating Representation from Reconstruction Enables Scalable Text Encoders Perception Encoder: The best visual embeddings are not at the output of the network

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5d8635c-6d00-4c5c-9886-d8d9a71eeca5 · outbound

This paper cites EVA-CLIP: Improved Training Techniques for CLIP at Scale.

Separating Representation from Reconstruction Enables Scalable Text Encoders EVA-CLIP: Improved Training Techniques for CLIP at Scale

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Unavailable: canonical work link unavailable.

Observation 3e42ed0a-fbbf-4cfb-abf2-0b802c7f26de · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

Separating Representation from Reconstruction Enables Scalable Text Encoders Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08cc1f4a-46c8-4d2a-8827-2988d0a8adeb · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Separating Representation from Reconstruction Enables Scalable Text Encoders RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c9fb3e8-4364-4fda-9516-886ce5659f61 · outbound

This paper cites Advances in neural information processing systems , volume=.

Separating Representation from Reconstruction Enables Scalable Text Encoders Advances in neural information processing systems , volume=

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation e2c902cc-df0e-41b8-8594-f4c2d509056f · outbound

This paper cites an unresolved cited work.

Separating Representation from Reconstruction Enables Scalable Text Encoders Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 5216b7e0-d826-4e48-8605-124bd966a756 · outbound

This paper cites BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models.

Separating Representation from Reconstruction Enables Scalable Text Encoders BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 1a909210-018b-4196-98e4-82de565646d5 · outbound

This paper cites Scaling Laws for Neural Language Models.

Separating Representation from Reconstruction Enables Scalable Text Encoders Scaling Laws for Neural Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation f4da7a38-a7ed-47fe-a9f3-3c585fcb5f48 · outbound

This paper cites and Sifre, Laurent , title =.

Separating Representation from Reconstruction Enables Scalable Text Encoders and Sifre, Laurent , title =

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation e2d2898d-a5c9-4571-a03a-3a4bc30675f3 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Separating Representation from Reconstruction Enables Scalable Text Encoders DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Unavailable: canonical work link unavailable.

Observation 5afe7ad2-b0fc-424d-afc7-d3a3a7d81422 · outbound

This paper cites Language models scale reliably with over-training and on downstream tasks.

Separating Representation from Reconstruction Enables Scalable Text Encoders Language models scale reliably with over-training and on downstream tasks

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5020cd9c-3c71-4129-8527-b8b8db863df2 · outbound

This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

Separating Representation from Reconstruction Enables Scalable Text Encoders Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88cd7eef-cdf1-4551-b21a-74539cf44f51 · outbound

This paper cites Journal of machine learning research , volume=.

Separating Representation from Reconstruction Enables Scalable Text Encoders Journal of machine learning research , volume=

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Unavailable: canonical work link unavailable.

Observation 5230b686-ce9a-4045-99ae-c79d157e59ce · outbound

This paper cites SimCSE: Simple Contrastive Learning of Sentence Embeddings.

Separating Representation from Reconstruction Enables Scalable Text Encoders SimCSE: Simple Contrastive Learning of Sentence Embeddings

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Unavailable: canonical work link unavailable.

Observation d74ece71-b0d8-4cef-9942-b4e02ae7c108 · outbound

This paper cites Towards General Text Embeddings with Multi-stage Contrastive Learning.

Separating Representation from Reconstruction Enables Scalable Text Encoders Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 93981c5f-898f-4d7b-be0f-97b0420b5cc2 · outbound

This paper cites Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics , pages=.

Separating Representation from Reconstruction Enables Scalable Text Encoders Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics , pages=

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ab70ef9-b7ae-4f03-8ce0-fa9ce811bac7 · outbound

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Separating Representation from Reconstruction Enables Scalable Text Encoders 2020 , eprint=

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation bcc744ac-c545-4b43-b3b9-4e68fe6ca1a8 · outbound

This paper cites 2023 , eprint=.

Separating Representation from Reconstruction Enables Scalable Text Encoders 2023 , eprint=

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-11T22:20:52.422988Z

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Observation 046de455-fdae-4f44-b8df-ac7a9ef7fda9 · outbound

This paper cites Are ELECTRA ' s Sentence Embeddings Beyond Repair? The Case of Semantic Textual Similarity.

Separating Representation from Reconstruction Enables Scalable Text Encoders Are ELECTRA ' s Sentence Embeddings Beyond Repair? The Case of Semantic Textual Similarity

Reference 41

Resolution: verified exact; doi, observed 2026-07-11T22:28:20.487537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.