Paper Citation Record · LEDGER

Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2410.10814.

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

pith.paper-citation-record.v1
2410.10814 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 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 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:20:23.650682Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:59:51.653811Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
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 e6a23bff-c653-4453-af4b-4e238e4ecb09 · inbound

Training Sparse Mixture Of Experts Text Embedding Models cites this paper.

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e55ed76-1e29-4eb2-9450-f90455ede7fd · inbound

ORI: O Routing Intelligence cites this paper.

ORI: O Routing Intelligence Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T19:40:07.609676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e5b5236-8c58-4772-a91a-c7597d47907c · inbound

Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs cites this paper.

Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T11:16:27.790734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c05b7aee-3340-4542-bd3c-7c545532fab6 · inbound

Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning cites this paper.

Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T05:18:25.166188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 041d7761-56f6-4aac-bcf9-b37fbaa20d19 · inbound

GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture cites this paper.

GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:25.205882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16c5c855-997c-46f1-a7ea-85d38f328d70 · inbound

MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security cites this paper.

MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-04T23:09:41.545861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30cadabc-ddc5-4868-9062-92e8b27b321a · inbound

FreeRet: MLLMs as Training-Free Retrievers cites this paper.

FreeRet: MLLMs as Training-Free Retrievers Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:01:23.466681Z

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.

Observation 26fba614-591f-48ed-8ef3-7fa053f843ee · inbound

FreeRet: MLLMs as Training-Free Retrievers cites this paper.

FreeRet: MLLMs as Training-Free Retrievers Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T13:51:45.593825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef86f980-9d7c-4e0c-a8a2-de15c80d46b8 · inbound

Breaking the MoE LLM Trilemma: Dynamic Expert Clustering with Structured Compression cites this paper.

Breaking the MoE LLM Trilemma: Dynamic Expert Clustering with Structured Compression Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T14:50:28.006100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1891de3a-35c9-4919-b431-4e56243b726a · inbound

Towards Explainable Adjudicative Variance: Quantifying Judicial Discretion via Gated Multi-Task Learning cites this paper.

Towards Explainable Adjudicative Variance: Quantifying Judicial Discretion via Gated Multi-Task Learning Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T13:59:51.655419Z

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.

Observation 6cb3a97f-3fc7-4121-ad54-3e90552c1702 · inbound

Towards Explainable Adjudicative Variance: Quantifying Judicial Discretion via Gated Multi-Task Learning cites this paper.

Towards Explainable Adjudicative Variance: Quantifying Judicial Discretion via Gated Multi-Task Learning Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T19:13:53.369413Z

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.