Paper Citation Record · LEDGER

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering

As of 18 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2505.12831.

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

pith.paper-citation-record.v1
2505.12831 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:29:59.815031Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:53:05.910963Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T14:53:06.190428Z

Reference resolution

52 of 52 outbound references displayed

verified exact1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 82044617-e2b4-4f94-a160-4901d6e6739d · outbound

This paper cites Cer, Mona T.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Cer, Mona T

Reference 1

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Observation 309c589b-274a-49d6-b78e-3fc71a77b152 · outbound

This paper cites Cer, Mona T.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Cer, Mona T

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T20:29:59.573080Z

Source-reported events for the cited work

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Observation 39b72d7f-fee7-4e61-95dc-daa63d1d9821 · outbound

This paper cites Cer, Mona T.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Cer, Mona T

Reference 3

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Source-reported events for the cited work

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Observation bc95884e-8b88-452c-80a5-c79f7a70a779 · outbound

This paper cites Cer, Mona T.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Cer, Mona T

Reference 4

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Observation d6117993-8d80-44e5-9e7b-fdfa11903bb0 · outbound

This paper cites Cer, Mona T.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Cer, Mona T

Reference 5

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Observation c5b0f0b1-7f07-4c46-9135-5b7008db5811 · outbound

This paper cites LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders

Reference 6

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Observation aa7d9431-03d0-4eb1-b96d-217e779dbd12 · outbound

This paper cites SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:29:59.598636Z

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Observation 43f9898e-fc08-40f3-9795-1b3b2e4a8644 · outbound

This paper cites an unresolved cited work.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 8

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Source-reported events for the cited work

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Observation 70aa8444-7091-4439-bfa5-e6f315313293 · outbound

This paper cites Multi-Prompting Decoder Helps Better Language Understanding.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Multi-Prompting Decoder Helps Better Language Understanding

Reference 9

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Observation ded6074d-be9a-43a0-bee0-24ed19dfb5a3 · outbound

This paper cites A Debiased Nearest Neighbors Framework for Multi-Label Text Classification.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering A Debiased Nearest Neighbors Framework for Multi-Label Text Classification

Reference 10

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Observation e29977c0-5685-46a6-bf6d-300b6957518d · outbound

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 11

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Observation 5f1ef7c2-2a01-48fd-b234-58321c08e1f6 · outbound

This paper cites an unresolved cited work.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 12

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Observation ab089d52-5446-434a-bc74-e1e706318e7f · outbound

This paper cites The Llama 3 Herd of Models.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering The Llama 3 Herd of Models

Reference 13

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Observation 8b944f9c-6be8-4400-815b-6e2098a9f5c9 · outbound

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 14

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Observation 29a52d11-863d-4a67-99b8-e0cc58ce3f1b · outbound

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

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs

Reference 15

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This paper cites an unresolved cited work.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 16

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 17

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Observation 963c0961-482d-45c1-a8a9-8db4b9da8e34 · outbound

This paper cites Scaling Sentence Embeddings with Large Language Models.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Scaling Sentence Embeddings with Large Language Models

Reference 18

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Observation 3b8b767b-89e3-4124-8347-d886806eddbf · outbound

This paper cites an unresolved cited work.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 19

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Observation 445961d5-2a60-45c4-9f88-d197aaa54fd4 · outbound

This paper cites Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?

Reference 20

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Observation 20768e49-f227-4ac0-aa71-d157e6dc00da · outbound

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

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 21

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Observation 6fab785b-0c79-4aff-861e-33bdf0e663f5 · outbound

This paper cites Meta-Task Prompting Elicits Embeddings from Large Language Models.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Meta-Task Prompting Elicits Embeddings from Large Language Models

Reference 22

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 23

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Observation 5a3f5893-2392-4473-8453-7574984848ce · outbound

This paper cites Vi \' e gas, Hanspeter Pfister, and Martin Wattenberg.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Vi \' e gas, Hanspeter Pfister, and Martin Wattenberg

Reference 24

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Observation c51053ea-7560-4ff4-9599-051989067f2a · outbound

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 25

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Observation 35e8a653-7887-43bc-9bb2-38ca422388f9 · outbound

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 26

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Observation 71836464-4fc6-490c-a052-c1827c7fcaa6 · outbound

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 27

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Observation 7c4a2082-60cc-44af-b04c-c21a879719b5 · outbound

This paper cites Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 28

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

Reference 29

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Generative Representational Instruction Tuning

Reference 30

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This paper cites MTEB: Massive Text Embedding Benchmark.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering MTEB: Massive Text Embedding Benchmark

Reference 31

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Hall, Daniel Cer, and Yinfei Yang

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Repetition Improves Language Model Embeddings

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Smith, Luke Zettlemoyer, and Tao Yu

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 43

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This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 44

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Unresolved cited work

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Simple Techniques for Enhancing Sentence Embeddings in Generative Language Models

Reference 48

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Starbucks-v2: Improved Training for 2D Matryoshka Embeddings

Reference 49

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Representation Engineering: A Top-Down Approach to AI Transparency

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering online" 'onlinestring :=

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Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering write newline

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Pith citing papers

Observation 583693af-66e4-4723-9206-1fad1f4e1218 · 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 Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering

Reference 2025

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Source-reported events for the cited work

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