Paper Citation Record · LEDGER

Training Sparse Mixture Of Experts Text Embedding Models

As of 9 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 16 inbound Pith citation observations for arXiv:2502.07972.

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

pith.paper-citation-record.v1
2502.07972 v3

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:20:23.727254Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:09:37.299547Z

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

30 of 30 outbound references displayed

verified exact1
verified fuzzy0
unresolved28
parse uncertain0
malformed identifier0
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External citation measurements

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

Outbound references

Observation 99384180-b8a9-4ab8-a0b7-1a9605377599 · outbound

This paper cites MegaBlocks: Efficient Sparse Training with Mixture-of-Experts.

Training Sparse Mixture Of Experts Text Embedding Models MegaBlocks: Efficient Sparse Training with Mixture-of-Experts

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.608575Z

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Observation 7bb68461-a936-4dba-8917-6622772dba58 · outbound

This paper cites Towards Inducing Long-Context Abilities in Multilingual Neural Machine Translation Models.

Training Sparse Mixture Of Experts Text Embedding Models Towards Inducing Long-Context Abilities in Multilingual Neural Machine Translation Models

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T11:20:24.097626Z

Source-reported events for the cited work

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Observation 384a544c-2ef0-4d7a-990e-6cba2d74fcd1 · outbound

This paper cites Contrastive Learning and Mixture of Experts Enables Precise Vector Embeddings.

Training Sparse Mixture Of Experts Text Embedding Models Contrastive Learning and Mixture of Experts Enables Precise Vector Embeddings

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-08T11:20:24.077151Z

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Observation 55cd9535-3e4b-4db5-aaa9-f9f4f0b56bfc · outbound

This paper cites Scaling Laws for Fine-Grained Mixture of Experts.

Training Sparse Mixture Of Experts Text Embedding Models Scaling Laws for Fine-Grained Mixture of Experts

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.633073Z

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Observation c6375d30-3663-4d97-ae60-5cf9a1147d6e · outbound

This paper cites Matryoshka Representation Learning.

Training Sparse Mixture Of Experts Text Embedding Models Matryoshka Representation Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.637406Z

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Observation 1aeeae6d-f7bf-4603-a6bc-12fd57a198a9 · outbound

This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

Training Sparse Mixture Of Experts Text Embedding Models GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.646455Z

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Observation e6a23bff-c653-4453-af4b-4e238e4ecb09 · outbound

This paper cites Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free.

Training Sparse Mixture Of Experts Text Embedding Models Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.650682Z

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Observation 46868ceb-b944-4504-87b5-9aace9e934ad · outbound

This paper cites Scaling Laws of RoPE-based Extrapolation.

Training Sparse Mixture Of Experts Text Embedding Models Scaling Laws of RoPE-based Extrapolation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.654929Z

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Observation ef32c99f-837a-4a31-b1ba-0726eeed4a31 · outbound

This paper cites Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models.

Training Sparse Mixture Of Experts Text Embedding Models Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.659224Z

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Observation 44b0d999-908d-4f47-83f6-ad96c0cba4f6 · outbound

This paper cites Generative Representational Instruction Tuning.

Training Sparse Mixture Of Experts Text Embedding Models Generative Representational Instruction Tuning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.663259Z

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Observation b2fba75c-34fc-4247-8982-85c0cb330d0a · outbound

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

Training Sparse Mixture Of Experts Text Embedding Models Nomic Embed: Training a Reproducible Long Context Text Embedder

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.667474Z

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Observation 7f36c2b0-9d83-4fdc-85ed-6f5f58e6045d · outbound

This paper cites an unresolved cited work.

Training Sparse Mixture Of Experts Text Embedding Models Unresolved cited work

Reference 19

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Observation 06569a7d-5833-4062-adf8-9536bffacb91 · outbound

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

Training Sparse Mixture Of Experts Text Embedding Models Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.690040Z

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Observation 6eebe7a1-b207-484b-87a6-a3814d399276 · outbound

This paper cites C-Pack: Packed Resources For General Chinese Embeddings.

Training Sparse Mixture Of Experts Text Embedding Models C-Pack: Packed Resources For General Chinese Embeddings

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.694453Z

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Observation 87cf181b-9fce-4008-b8a2-ed9fabef6bc7 · outbound

This paper cites Effective Long-Context Scaling of Foundation Models.

Training Sparse Mixture Of Experts Text Embedding Models Effective Long-Context Scaling of Foundation Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.698827Z

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Observation 00c4a738-7e39-4c19-b7cf-4febec0037d1 · outbound

This paper cites mT5: A massively multilingual pre-trained text-to-text transformer.

Training Sparse Mixture Of Experts Text Embedding Models mT5: A massively multilingual pre-trained text-to-text transformer

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.703288Z

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Observation f8767e89-f3cb-4ffc-8460-47e4a65333e5 · outbound

This paper cites Arctic-Embed 2.0: Multilingual Retrieval Without Compromise.

Training Sparse Mixture Of Experts Text Embedding Models Arctic-Embed 2.0: Multilingual Retrieval Without Compromise

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.708490Z

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Observation 4a95c4dd-5bcf-4ff8-bb8c-e0d1a6d98e37 · outbound

This paper cites Making a MIRACL: Multilingual Information Retrieval Across a Continuum of Languages.

Training Sparse Mixture Of Experts Text Embedding Models Making a MIRACL: Multilingual Information Retrieval Across a Continuum of Languages

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.718168Z

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Observation 8522fc91-cc67-49f1-b963-fa29b1151f0a · outbound

This paper cites mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval.

Training Sparse Mixture Of Experts Text Embedding Models mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.722732Z

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Observation 5bc7a076-1f82-41ba-92ca-bb5ca0b6784c · outbound

This paper cites ST-MoE: Designing Stable and Transferable Sparse Expert Models.

Training Sparse Mixture Of Experts Text Embedding Models ST-MoE: Designing Stable and Transferable Sparse Expert Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.727254Z

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Observation 7ea765dc-bc22-411b-868f-b111aa85369f · outbound

This paper cites doi: 10.1162/neco.1997.9.8.1735.

Training Sparse Mixture Of Experts Text Embedding Models doi: 10.1162/neco.1997.9.8.1735

Reference 1997

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.623356Z

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Observation b10bb9fd-d50f-4248-b7c3-ba34a582fdbb · outbound

This paper cites doi: 10.18653/v1/D16-1264.

Training Sparse Mixture Of Experts Text Embedding Models doi: 10.18653/v1/D16-1264

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.671913Z

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Observation 8428ffdb-bad7-4455-bcbc-f7e83beef7f1 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Training Sparse Mixture Of Experts Text Embedding Models Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.685607Z

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Observation 58946727-309e-49e1-b5c5-632f98eeb282 · outbound

This paper cites NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models.

Training Sparse Mixture Of Experts Text Embedding Models NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.641838Z

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Observation ecb0018a-1d83-4c84-8e04-bc3731464401 · outbound

This paper cites Unsupervised Cross-lingual Representation Learning at Scale.

Training Sparse Mixture Of Experts Text Embedding Models Unsupervised Cross-lingual Representation Learning at Scale

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.598316Z

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Observation c6e4e0bf-2868-4cc0-8abd-2a953ebc31bc · outbound

This paper cites XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation.

Training Sparse Mixture Of Experts Text Embedding Models XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.681129Z

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Observation 4d7f054e-711a-4138-8d5d-f1144ade91be · outbound

This paper cites Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity.

Training Sparse Mixture Of Experts Text Embedding Models Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.603364Z

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Observation 04f50ded-00a7-460e-935f-a8e016755d0e · outbound

This paper cites Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints.

Training Sparse Mixture Of Experts Text Embedding Models Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints

Reference 2023

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Observation 0797a83d-761a-49f1-9c8e-6bbdc8b5a63a · outbound

This paper cites M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation.

Training Sparse Mixture Of Experts Text Embedding Models M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.592597Z

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Observation eae619b5-756b-464e-93be-aceaccd2605b · outbound

This paper cites Jasper and Stella: distillation of SOTA embedding models.

Training Sparse Mixture Of Experts Text Embedding Models Jasper and Stella: distillation of SOTA embedding models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-08T11:20:23.713428Z

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Pith citing papers

Observation cf30f101-c72a-4ed6-b41e-2791dd8ea6ae · inbound

Chunk Twice, Embed Once: A Systematic Study of Segmentation and Representation Trade-offs in Chemistry-Aware Retrieval-Augmented Generation cites this paper.

Chunk Twice, Embed Once: A Systematic Study of Segmentation and Representation Trade-offs in Chemistry-Aware Retrieval-Augmented Generation Training Sparse Mixture Of Experts Text Embedding Models

Reference 2024

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Omnilingual SONAR: Cross-Lingual and Cross-Modal Sentence Embeddings Bridging Massively Multilingual Text and Speech cites this paper.

Omnilingual SONAR: Cross-Lingual and Cross-Modal Sentence Embeddings Bridging Massively Multilingual Text and Speech Training Sparse Mixture Of Experts Text Embedding Models

Reference 7

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Spectral Tempering for Embedding Compression in Dense Passage Retrieval cites this paper.

Spectral Tempering for Embedding Compression in Dense Passage Retrieval Training Sparse Mixture Of Experts Text Embedding Models

Reference 30

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Source-reported events for the cited work

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Observation fead9e2f-4eb9-416e-ab81-37ddf4c1d24e · inbound

Data Mixing for Large Language Models Pretraining: A Survey and Outlook cites this paper.

Data Mixing for Large Language Models Pretraining: A Survey and Outlook Training Sparse Mixture Of Experts Text Embedding Models

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:58:25.729802Z

Source-reported events for the cited work

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Observation a5ae6bb7-866e-4369-a067-e1f3bcc68389 · inbound

Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior in Generative Retrieval cites this paper.

Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior in Generative Retrieval Training Sparse Mixture Of Experts Text Embedding Models

Reference 24

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Observation 575c7cdd-479d-4de9-97d1-2b58a10fb72a · inbound

IdioLink: Retrieving Meaning Beyond Words Across Idiomatic and Literal Expressions cites this paper.

IdioLink: Retrieving Meaning Beyond Words Across Idiomatic and Literal Expressions Training Sparse Mixture Of Experts Text Embedding Models

Reference 38

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Argus-Retriever: Vision-LLM Late-Interaction Retrieval with Region-Aware Query-Conditioned MoE for Visual Document Retrieval cites this paper.

Argus-Retriever: Vision-LLM Late-Interaction Retrieval with Region-Aware Query-Conditioned MoE for Visual Document Retrieval Training Sparse Mixture Of Experts Text Embedding Models

Reference 23

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Observation 502e1960-b713-4c04-a950-739d6c4bf0dd · inbound

Zero-Shot Semantic Re-Identification for Autonomous Driving: A VLM Baseline Study cites this paper.

Zero-Shot Semantic Re-Identification for Autonomous Driving: A VLM Baseline Study Training Sparse Mixture Of Experts Text Embedding Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:57:30.713888Z

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Observation 1825692e-eda8-4721-8ae2-3d96854d9c11 · inbound

SkMTEB: Slovak Massive Text Embedding Benchmark and Model Adaptation cites this paper.

SkMTEB: Slovak Massive Text Embedding Benchmark and Model Adaptation Training Sparse Mixture Of Experts Text Embedding Models

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T15:08:33.561685Z

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Observation 466197c9-5be8-425e-a487-465b1a8bfe9d · inbound

HistoRAG: Embedding Historical Methodology in Retrieval-Augmented Generation Through Critical Technical Practice cites this paper.

HistoRAG: Embedding Historical Methodology in Retrieval-Augmented Generation Through Critical Technical Practice Training Sparse Mixture Of Experts Text Embedding Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-06-27T00:30:16.214827Z

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Observation 2ad7d3b8-87b4-40f2-a4c2-f6df9bb53879 · inbound

A Comparative Study on Affective Cues in Text Embeddings Across Psychological Emotion Theories cites this paper.

A Comparative Study on Affective Cues in Text Embeddings Across Psychological Emotion Theories Training Sparse Mixture Of Experts Text Embedding Models

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T09:24:31.783236Z

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Observation 96c0b6e0-0d18-47a4-81a9-025d7041ae2a · inbound

Evaluating Chunking Strategies for Retrieval-Augmented Generation on Academic Texts cites this paper.

Evaluating Chunking Strategies for Retrieval-Augmented Generation on Academic Texts Training Sparse Mixture Of Experts Text Embedding Models

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-03T06:57:42.250266Z

Source-reported events for the cited work

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Observation 0b7990bf-4b0d-4cbb-b8b1-67a6bc1133e1 · inbound

OntoLearner: A Modular Python Library for Ontology Learning with Large Language Models cites this paper.

OntoLearner: A Modular Python Library for Ontology Learning with Large Language Models Training Sparse Mixture Of Experts Text Embedding Models

Reference 14

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Observation 91b6023f-1c3e-463e-9f97-b6a99fbaff4b · inbound

MARS: Multi-hop Adaptive Retrieval and SPARQL Generation for KGQA cites this paper.

MARS: Multi-hop Adaptive Retrieval and SPARQL Generation for KGQA Training Sparse Mixture Of Experts Text Embedding Models

Reference 35

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Observation a5781c60-9705-4831-b0c5-6d0a12d529c9 · inbound

A Comparative Evaluation of Embeddings and LLMs in a Greek Book Publisher Setting - The CUP Dataset cites this paper.

A Comparative Evaluation of Embeddings and LLMs in a Greek Book Publisher Setting - The CUP Dataset Training Sparse Mixture Of Experts Text Embedding Models

Reference 12

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Continuous Online Evaluation of Recommendation Strategies in Social Science Academic Search cites this paper.

Continuous Online Evaluation of Recommendation Strategies in Social Science Academic Search Training Sparse Mixture Of Experts Text Embedding Models

Reference 58

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