Paper Citation Record · LEDGER

Repetition Improves Language Model Embeddings

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2402.15449.

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

pith.paper-citation-record.v1
2402.15449 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:29:35.320059Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T15:18:32.790599Z

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 c09a4ac0-ee53-496f-a8dc-e44c34ae2e31 · inbound

VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks cites this paper.

VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks Repetition Improves Language Model Embeddings

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-17T21:19:44.017773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 94e9643c-0787-4f63-946a-5978b19a6667 · inbound

Are Decoder-Only Large Language Models the Silver Bullet for Code Search? cites this paper.

Are Decoder-Only Large Language Models the Silver Bullet for Code Search? Repetition Improves Language Model Embeddings

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-23T18:43:19.277050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b94bf483-407b-4f26-b040-3338f133aeb3 · inbound

FLAME: Frozen Large Language Models Enable Data-Efficient Language-Image Pre-training cites this paper.

FLAME: Frozen Large Language Models Enable Data-Efficient Language-Image Pre-training Repetition Improves Language Model Embeddings

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T18:38:18.973434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f665b67-7b9d-4602-9ae0-3b424173a7cc · inbound

Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs cites this paper.

Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs Repetition Improves Language Model Embeddings

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T14:53:05.967185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba503977-97d5-4273-96d7-2a90c8570dcc · inbound

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

LLMs are Also Effective Embedding Models: An In-depth Overview Repetition Improves Language Model Embeddings

Reference 143

Resolution: unresolved; no resolver link, observed 2026-08-11T13:59:01.909295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b372e310-ec1c-4ca0-9aca-53629e7d20a4 · inbound

ExLM: Rethinking the Impact of [MASK] Tokens in Masked Language Models cites this paper.

ExLM: Rethinking the Impact of [MASK] Tokens in Masked Language Models Repetition Improves Language Model Embeddings

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T16:17:32.141217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1897d090-2367-4aa5-b13f-c95ac0c20c83 · inbound

Redundancy, Isotropy, and Intrinsic Dimensionality of Prompt-based Text Embeddings cites this paper.

Redundancy, Isotropy, and Intrinsic Dimensionality of Prompt-based Text Embeddings Repetition Improves Language Model Embeddings

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T11:49:15.783858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5fc8218-d8a9-436b-aaa5-576f9ff075c9 · inbound

GEM: Empowering LLM for both Embedding Generation and Language Understanding cites this paper.

GEM: Empowering LLM for both Embedding Generation and Language Understanding Repetition Improves Language Model Embeddings

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.906275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 554f8853-d4a0-49a4-9075-33be8ee69c87 · inbound

A Comprehensive Study of Decoder-Only LLMs for Text-to-Image Generation cites this paper.

A Comprehensive Study of Decoder-Only LLMs for Text-to-Image Generation Repetition Improves Language Model Embeddings

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:51.173283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 325846b2-21cb-47b8-a26c-da11d3ce13b7 · 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 Repetition Improves Language Model Embeddings

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-07T05:18:29.702634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6be4204e-594e-40f4-85f4-2b067c70146a · inbound

DeepRTL2: A Versatile Model for RTL-Related Tasks cites this paper.

DeepRTL2: A Versatile Model for RTL-Related Tasks Repetition Improves Language Model Embeddings

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T13:18:32.573515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6eecbe36-db5a-48ff-9a44-a0551405457a · inbound

Should We Still Pretrain Encoders with Masked Language Modeling? cites this paper.

Should We Still Pretrain Encoders with Masked Language Modeling? Repetition Improves Language Model Embeddings

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-19T06:32:07.671224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 03d33564-cf56-463a-9820-41613b9a77df · inbound

A Comparative Study of Specialized LLMs as Dense Retrievers cites this paper.

A Comparative Study of Specialized LLMs as Dense Retrievers Repetition Improves Language Model Embeddings

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T20:02:17.545554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcbcbedd-2591-45cb-9cc1-22ced9d2bdc5 · inbound

BiXSE: Improving Dense Retrieval via Probabilistic Graded Relevance Distillation cites this paper.

BiXSE: Improving Dense Retrieval via Probabilistic Graded Relevance Distillation Repetition Improves Language Model Embeddings

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T22:36:59.935632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b14a890-e01d-43b7-a6a8-ee613d1820c0 · inbound

Autoregressive Universal Video Segmentation Model cites this paper.

Autoregressive Universal Video Segmentation Model Repetition Improves Language Model Embeddings

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T15:52:16.597131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c0647da-fb15-444b-ad50-4730438d39a0 · inbound

QZhou-Embedding Technical Report cites this paper.

QZhou-Embedding Technical Report Repetition Improves Language Model Embeddings

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T14:11:05.627144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04e4f75b-7c82-4fc7-8d66-f30ac71a057b · inbound

Exploring Reasoning-Infused Text Embedding with Large Language Models for Zero-Shot Dense Retrieval cites this paper.

Exploring Reasoning-Infused Text Embedding with Large Language Models for Zero-Shot Dense Retrieval Repetition Improves Language Model Embeddings

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T13:50:11.502258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f47df09-5c56-4115-b462-dbb095a94672 · inbound

Negative Matters: Multi-Granularity Hard-Negative Synthesis and Anchor-Token-Aware Pooling for Enhanced Text Embeddings cites this paper.

Negative Matters: Multi-Granularity Hard-Negative Synthesis and Anchor-Token-Aware Pooling for Enhanced Text Embeddings Repetition Improves Language Model Embeddings

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T13:16:26.814247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcaeb7aa-0366-4b15-ae8e-24aca42d4aeb · inbound

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

FreeRet: MLLMs as Training-Free Retrievers Repetition Improves Language Model Embeddings

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:01:23.423722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a8716cb6-480b-48bb-ae76-b9d70901cb20 · inbound

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

FreeRet: MLLMs as Training-Free Retrievers Repetition Improves Language Model Embeddings

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T13:51:46.748960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b6cbc24-7214-44b9-abd9-ec76eea1923d · inbound

Latent Abstraction for Retrieval-Augmented Generation cites this paper.

Latent Abstraction for Retrieval-Augmented Generation Repetition Improves Language Model Embeddings

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:01:04.921789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bb8c55e4-a889-4cb8-8663-66293de7eaf3 · inbound

ReverseEOL: Improving Training-free Text Embeddings via Text Reversal in Decoder-only LLMs cites this paper.

ReverseEOL: Improving Training-free Text Embeddings via Text Reversal in Decoder-only LLMs Repetition Improves Language Model Embeddings

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T12:56:57.170565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d0ebb9b5-b233-4598-a4a9-adff4ef03685 · inbound

PARTREP: Learning What to Repeat for Decoder-only LLMs cites this paper.

PARTREP: Learning What to Repeat for Decoder-only LLMs Repetition Improves Language Model Embeddings

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T15:18:32.792390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 85f86a28-41b5-497d-a7c6-ea630e64f244 · inbound

Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes cites this paper.

Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes Repetition Improves Language Model Embeddings

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-04T07:49:39.872462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d81a4c18-56fd-455d-b8ff-d78d391ede5e · inbound

Tevatron-Elastic: A Unified Abstraction for Training Elastic Retrievers and Rerankers cites this paper.

Tevatron-Elastic: A Unified Abstraction for Training Elastic Retrievers and Rerankers Repetition Improves Language Model Embeddings

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-14T04:29:35.320059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.