Paper Citation Record · LEDGER

GenEOL: Harnessing the Generative Power of LLMs for Training-Free Sentence Embeddings

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.14635.

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

pith.paper-citation-record.v1
2410.14635 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:59:01.946755Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T08:13:15.122614Z

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 9a6583a7-bf68-4303-b098-d025ec64c436 · inbound

LLMs are Also Effective Embedding Models: An In-depth Overview cites this paper.

LLMs are Also Effective Embedding Models: An In-depth Overview GenEOL: Harnessing the Generative Power of LLMs for Training-Free Sentence Embeddings

Reference 157

Resolution: unresolved; no resolver link, observed 2026-08-11T13:59:01.946755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6938b10-9873-47e2-bd78-d01cf049969a · 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 GenEOL: Harnessing the Generative Power of LLMs for Training-Free Sentence Embeddings

Reference 105

Resolution: unresolved; no resolver link, observed 2026-08-07T05:18:31.132234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fea2b45c-4079-45a1-8aa5-8c0892bf985a · inbound

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

FreeRet: MLLMs as Training-Free Retrievers GenEOL: Harnessing the Generative Power of LLMs for Training-Free Sentence Embeddings

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:01:23.527643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0bade4ad-4e8a-4c62-b53f-eca4b9a6df2b · inbound

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

FreeRet: MLLMs as Training-Free Retrievers GenEOL: Harnessing the Generative Power of LLMs for Training-Free Sentence Embeddings

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T13:51:47.066669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a53e4027-7340-40b0-98aa-17e841b21e6e · inbound

mEOL: Training-Free Instruction-Guided Multimodal Embedder for Vector Graphics and Image Retrieval cites this paper.

mEOL: Training-Free Instruction-Guided Multimodal Embedder for Vector Graphics and Image Retrieval GenEOL: Harnessing the Generative Power of LLMs for Training-Free Sentence Embeddings

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:51:46.462598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 31dbcdb3-0329-4f2c-b88f-e038df581722 · inbound

DocRetriever: A Plug-and-Play Framework for Multimodal Document Retrieval with Comprehensive Benchmark cites this paper.

DocRetriever: A Plug-and-Play Framework for Multimodal Document Retrieval with Comprehensive Benchmark GenEOL: Harnessing the Generative Power of LLMs for Training-Free Sentence Embeddings

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:13:15.124343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.