Improving Text Embeddings with Large Language Models | Paper Citation Record

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

M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation Improving Text Embeddings with Large Language Models

Reference 15

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Observation e2fee14a-80d5-4bb9-aad0-b48c2fdcfea1 · inbound

Multilingual E5 Text Embeddings: A Technical Report cites this paper.

Multilingual E5 Text Embeddings: A Technical Report Improving Text Embeddings with Large Language Models

Reference 50

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Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models cites this paper.

Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models Improving Text Embeddings with Large Language Models

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-15T23:32:17.983739Z

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Observation fa90f418-66cf-4d1e-9aa2-3043fd1b547e · inbound

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

NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models Improving Text Embeddings with Large Language Models

Reference 99

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Observation c924a345-fbd9-4c66-967e-a49f2678a870 · inbound

E5-V: Universal Embeddings with Multimodal Large Language Models cites this paper.

E5-V: Universal Embeddings with Multimodal Large Language Models Improving Text Embeddings with Large Language Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:52:21.001858Z

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Observation c103aa5f-1e81-425e-aba9-0795149e317e · 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? Improving Text Embeddings with Large Language Models

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-23T18:43:19.227770Z

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Observation f4b1d4fb-e627-441b-8657-49b3a678da88 · inbound

Syntriever: How to Train Your Retriever with Synthetic Data from LLMs cites this paper.

Syntriever: How to Train Your Retriever with Synthetic Data from LLMs Improving Text Embeddings with Large Language Models

Reference 50

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Observation d74de037-8040-45f3-9cd8-3200f4b5ed12 · inbound

Retrieval-augmented Large Language Models for Financial Time Series Forecasting cites this paper.

Retrieval-augmented Large Language Models for Financial Time Series Forecasting Improving Text Embeddings with Large Language Models

Reference 16

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Observation 78aaf3a2-2d0a-484e-adde-a464a25e234a · inbound

O1 Embedder: Let Retrievers Think Before Action cites this paper.

O1 Embedder: Let Retrievers Think Before Action Improving Text Embeddings with Large Language Models

Reference 55

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Observation db20dbd8-8643-4712-9eb8-4abc88908d73 · inbound

Universal Model Routing for Efficient LLM Inference cites this paper.

Universal Model Routing for Efficient LLM Inference Improving Text Embeddings with Large Language Models

Reference 116

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Observation abb67b2e-3704-4fff-9224-bbc03a3ff40d · inbound

Vortex: Overcoming Memory Capacity Limitations in GPU-Accelerated Large-Scale Data Analytics cites this paper.

Vortex: Overcoming Memory Capacity Limitations in GPU-Accelerated Large-Scale Data Analytics Improving Text Embeddings with Large Language Models

Reference 54

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Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective cites this paper.

Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective Improving Text Embeddings with Large Language Models

Reference 38

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Observation ce4d13b4-9c94-4ff9-9fd5-36fd2fd7fdce · inbound

Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space cites this paper.

Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space Improving Text Embeddings with Large Language Models

Reference 26

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Observation e384db64-0cab-46e2-9783-70c736fd6276 · inbound

Hard Negative Mining for Domain-Specific Retrieval in Enterprise Systems cites this paper.

Hard Negative Mining for Domain-Specific Retrieval in Enterprise Systems Improving Text Embeddings with Large Language Models

Reference 54

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Observation e8f9687d-2ad2-46df-8af6-6e62e8a0b544 · inbound

Towards Better Instruction Following Retrieval Models cites this paper.

Towards Better Instruction Following Retrieval Models Improving Text Embeddings with Large Language Models

Reference 40

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Observation 969bdb56-241b-4bab-a755-d77de71cc2a3 · inbound

LazyVLM: Neuro-Symbolic Approach to Video Analytics cites this paper.

LazyVLM: Neuro-Symbolic Approach to Video Analytics Improving Text Embeddings with Large Language Models

Reference 10

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Observation c7a76184-41b5-42fb-92b6-c65ffc58160b · inbound

Principled Content Selection to Generate Diverse and Personalized Multi-Document Summaries cites this paper.

Principled Content Selection to Generate Diverse and Personalized Multi-Document Summaries Improving Text Embeddings with Large Language Models

Reference 48

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Observation 8b16a745-153f-4fd5-8d85-1b8233d59019 · inbound

GATE: General Arabic Text Embedding for Enhanced Semantic Textual Similarity with Matryoshka Representation Learning and Hybrid Loss Training cites this paper.

GATE: General Arabic Text Embedding for Enhanced Semantic Textual Similarity with Matryoshka Representation Learning and Hybrid Loss Training Improving Text Embeddings with Large Language Models

Reference 34

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Observation 399f11c7-faab-4907-b56f-6aa8db6023ba · inbound

Don't Reinvent the Wheel: Efficient Instruction-Following Text Embedding based on Guided Space Transformation cites this paper.

Don't Reinvent the Wheel: Efficient Instruction-Following Text Embedding based on Guided Space Transformation Improving Text Embeddings with Large Language Models

Reference 36

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Observation daede230-474e-4411-82d4-9d29a8a01e4a · inbound

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings cites this paper.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Improving Text Embeddings with Large Language Models

Reference 48

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Observation 4a2743b0-9c8d-4a98-a745-94a6b9ec0188 · inbound

Optimizing Question Semantic Space for Dynamic Retrieval-Augmented Multi-hop Question Answering cites this paper.

Optimizing Question Semantic Space for Dynamic Retrieval-Augmented Multi-hop Question Answering Improving Text Embeddings with Large Language Models

Reference 36

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Observation b2ce4c83-c7e1-41b5-a427-4df0cf8556a4 · inbound

Politics and polarization on Bluesky cites this paper.

Politics and polarization on Bluesky Improving Text Embeddings with Large Language Models

Reference 25

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Observation da6a8e7d-271b-48d6-a34e-3f8319f59583 · inbound

Establishing Trustworthy LLM Evaluation via Shortcut Neuron Analysis cites this paper.

Establishing Trustworthy LLM Evaluation via Shortcut Neuron Analysis Improving Text Embeddings with Large Language Models

Reference 41

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Observation daee0891-fe6b-4f0d-bed6-7ce2c8ff5b9c · inbound

Towards an Explainable Comparison and Alignment of Feature Embeddings cites this paper.

Towards an Explainable Comparison and Alignment of Feature Embeddings Improving Text Embeddings with Large Language Models

Reference 65

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Observation c447c6aa-76f1-4972-96af-101e2d2441a7 · inbound

LGAI-EMBEDDING-Preview Technical Report cites this paper.

LGAI-EMBEDDING-Preview Technical Report Improving Text Embeddings with Large Language Models

Reference 2

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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 Improving Text Embeddings with Large Language Models

Reference 111

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Observation c0a19b05-b275-44d0-9b21-0e04c722b89e · inbound

Combining Log Data and Collaborative Dialogue Features to Predict Project Quality in Middle School AI Education cites this paper.

Combining Log Data and Collaborative Dialogue Features to Predict Project Quality in Middle School AI Education Improving Text Embeddings with Large Language Models

Reference 53

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Observation a0227755-5e81-461f-8903-ac5d4e5731df · inbound

TongSearch-QR: Reinforced Query Reasoning for Retrieval cites this paper.

TongSearch-QR: Reinforced Query Reasoning for Retrieval Improving Text Embeddings with Large Language Models

Reference 34

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Observation cc3b28d5-6ef8-4682-a9ed-27341af16e6d · inbound

Maximally-Informative Retrieval for State Space Model Generation cites this paper.

Maximally-Informative Retrieval for State Space Model Generation Improving Text Embeddings with Large Language Models

Reference 31

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Observation c242fb8c-c011-44dc-a856-faea2a18b401 · inbound

Towards Building General Purpose Embedding Models for Industry 4.0 Agents cites this paper.

Towards Building General Purpose Embedding Models for Industry 4.0 Agents Improving Text Embeddings with Large Language Models

Reference 18

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Observation f050ab53-b2e5-4b18-99ee-a58868fdc82c · inbound

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

DeepRTL2: A Versatile Model for RTL-Related Tasks Improving Text Embeddings with Large Language Models

Reference 38

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QUST_NLP at SemEval-2025 Task 7: A Three-Stage Retrieval Framework for Monolingual and Crosslingual Fact-Checked Claim Retrieval cites this paper.

QUST_NLP at SemEval-2025 Task 7: A Three-Stage Retrieval Framework for Monolingual and Crosslingual Fact-Checked Claim Retrieval Improving Text Embeddings with Large Language Models

Reference 15

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Observation 8d3205fd-f7fd-4ac5-81ad-99c12b4ff1a2 · inbound

Data Curation Matters: Model Collapse and Spurious Shift Performance Prediction from Training on Uncurated Text Embeddings cites this paper.

Data Curation Matters: Model Collapse and Spurious Shift Performance Prediction from Training on Uncurated Text Embeddings Improving Text Embeddings with Large Language Models

Reference 16

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Observation 0bcf72c6-2cf5-418c-9edd-3971cd922f2a · inbound

CCRS: A Zero-Shot LLM-as-a-Judge Framework for Comprehensive RAG Evaluation cites this paper.

CCRS: A Zero-Shot LLM-as-a-Judge Framework for Comprehensive RAG Evaluation Improving Text Embeddings with Large Language Models

Reference 21

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Maintaining MTEB: Towards Long Term Usability and Reproducibility of Embedding Benchmarks cites this paper.

Maintaining MTEB: Towards Long Term Usability and Reproducibility of Embedding Benchmarks Improving Text Embeddings with Large Language Models

Reference 19

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Observation cedb1e69-68d1-476d-80de-dea42f136b79 · inbound

Scaling Self-Supervised Representation Learning for Symbolic Piano Performance cites this paper.

Scaling Self-Supervised Representation Learning for Symbolic Piano Performance Improving Text Embeddings with Large Language Models

Reference 76

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VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents cites this paper.

VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents Improving Text Embeddings with Large Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-18T14:10:15.124172Z

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Observation b46d6ff3-48bd-4bfe-98f2-a4b28ee47c6b · inbound

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model cites this paper.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Improving Text Embeddings with Large Language Models

Reference 4

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UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversations cites this paper.

UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversations Improving Text Embeddings with Large Language Models

Reference 60

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Observation 3c2d7ca4-a24e-4cee-9cb8-95869f728df5 · inbound

Improving Korean-English Cross-Lingual Retrieval: A Data-Centric Study of Language Composition and Model Merging cites this paper.

Improving Korean-English Cross-Lingual Retrieval: A Data-Centric Study of Language Composition and Model Merging Improving Text Embeddings with Large Language Models

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-22T00:40:50.957487Z

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Observation 70eabfbb-e08f-4e8b-8416-eb2172ffa91e · inbound

A Scalable and Efficient Signal Integration System for Job Matching cites this paper.

A Scalable and Efficient Signal Integration System for Job Matching Improving Text Embeddings with Large Language Models

Reference 42

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Observation da3b362a-5c0c-468c-812c-45fafcc917a2 · inbound

Automated Novelty Evaluation of Academic Paper: A Collaborative Approach Integrating Human and Large Language Model Knowledge cites this paper.

Automated Novelty Evaluation of Academic Paper: A Collaborative Approach Integrating Human and Large Language Model Knowledge Improving Text Embeddings with Large Language Models

Reference 64

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Observation 4ddc536b-abda-4163-aca8-cebacc2a6345 · inbound

Text-ADBench: Text Anomaly Detection Benchmark based on LLMs Embedding cites this paper.

Text-ADBench: Text Anomaly Detection Benchmark based on LLMs Embedding Improving Text Embeddings with Large Language Models

Reference 68

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Observation a723ef61-983e-485a-9945-1b4af9abe018 · inbound

Learning Robust Negation Text Representations cites this paper.

Learning Robust Negation Text Representations Improving Text Embeddings with Large Language Models

Reference 38

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Observation baaf771b-fa84-4c28-8d01-bd9f30ea098e · inbound

Traits Run Deep: Enhancing Personality Assessment via Psychology-Guided LLM Representations and Multimodal Apparent Behaviors cites this paper.

Traits Run Deep: Enhancing Personality Assessment via Psychology-Guided LLM Representations and Multimodal Apparent Behaviors Improving Text Embeddings with Large Language Models

Reference 45

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Observation e4e0310d-ddf8-406e-bcb5-64d396688bd4 · inbound

Semantic Compression for Word and Sentence Embeddings using Discrete Wavelet Transform cites this paper.

Semantic Compression for Word and Sentence Embeddings using Discrete Wavelet Transform Improving Text Embeddings with Large Language Models

Reference 56

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Observation 1597a469-a8a3-4c22-99a9-bf658e1e072f · inbound

BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent cites this paper.

BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent Improving Text Embeddings with Large Language Models

Reference 24

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Observation 4421920f-5bb6-4003-b3f8-d42696ee7531 · inbound

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

BiXSE: Improving Dense Retrieval via Probabilistic Graded Relevance Distillation Improving Text Embeddings with Large Language Models

Reference 31

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Observation 7103c237-fc05-4581-9391-104f25543616 · inbound

THEME: Enhancing Thematic Investing with Semantic Stock Representations and Temporal Dynamics cites this paper.

THEME: Enhancing Thematic Investing with Semantic Stock Representations and Temporal Dynamics Improving Text Embeddings with Large Language Models

Reference 23

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Observation 3dd65e80-2cef-4f3f-b055-5fa922196ec5 · inbound

S2Sent: Nested Selectivity Aware Sentence Representation Learning cites this paper.

S2Sent: Nested Selectivity Aware Sentence Representation Learning Improving Text Embeddings with Large Language Models

Reference 30

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Observation a93d5132-c71c-45ab-98bd-b70bfc948626 · inbound

Granite Embedding R2 Models cites this paper.

Granite Embedding R2 Models Improving Text Embeddings with Large Language Models

Reference 52

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Observation c43a5a14-6411-4d25-86cf-fdcfc809cd97 · inbound

QZhou-Embedding Technical Report cites this paper.

QZhou-Embedding Technical Report Improving Text Embeddings with Large Language Models

Reference 28

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Observation db22c125-11e3-4a1a-b573-72545f86c697 · inbound

NER Retriever: Zero-Shot Named Entity Retrieval with Type-Aware Embeddings cites this paper.

NER Retriever: Zero-Shot Named Entity Retrieval with Type-Aware Embeddings Improving Text Embeddings with Large Language Models

Reference 12

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Observation f8aef148-300a-44f9-863b-595854dac9f4 · inbound

No Thoughts Just AI: Biased LLM Hiring Recommendations Alter Human Decision Making and Limit Human Autonomy cites this paper.

No Thoughts Just AI: Biased LLM Hiring Recommendations Alter Human Decision Making and Limit Human Autonomy Improving Text Embeddings with Large Language Models

Reference 72

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Observation c41ff9e5-b32c-427b-88c6-19bbc96920f1 · inbound

Revealing the Numeracy Gap: An Empirical Investigation of Text Embedding Models cites this paper.

Revealing the Numeracy Gap: An Empirical Investigation of Text Embedding Models Improving Text Embeddings with Large Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T05:14:15.090294Z

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Observation d7cc9801-c457-4364-93c9-e4f86c556e8d · inbound

Retrofitting Small Multilingual Models for Retrieval: Matching 7B Performance with 300M Parameters cites this paper.

Retrofitting Small Multilingual Models for Retrieval: Matching 7B Performance with 300M Parameters Improving Text Embeddings with Large Language Models

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T07:01:01.610847Z

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Observation 386d9eb1-e481-4621-a922-c3db8264699f · inbound

Unified Work Embeddings: Contrastive Learning of a Bidirectional Multi-task Ranker cites this paper.

Unified Work Embeddings: Contrastive Learning of a Bidirectional Multi-task Ranker Improving Text Embeddings with Large Language Models

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:05:31.398870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9814885f-1e55-45ff-8aab-17a0069a4a7c · inbound

LPCAN: Lightweight Pyramid Cross-Attention Network for Rail Surface Defect Detection Using RGB-D Data cites this paper.

LPCAN: Lightweight Pyramid Cross-Attention Network for Rail Surface Defect Detection Using RGB-D Data Improving Text Embeddings with Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T10:43:49.939421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 132b7ebc-aeda-408e-910a-02019adf10b8 · inbound

Knowledge-Embedded and Hypernetwork-Guided Few-Shot Substation Meter Defect Image Generation Method cites this paper.

Knowledge-Embedded and Hypernetwork-Guided Few-Shot Substation Meter Defect Image Generation Method Improving Text Embeddings with Large Language Models

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-03T10:43:42.366926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7e820be-666d-43dc-b67a-d0582b08650f · inbound

Legal Retrieval for Public Defenders cites this paper.

Legal Retrieval for Public Defenders Improving Text Embeddings with Large Language Models

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-21T15:10:16.593802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e401695f-440c-47fa-85ef-1377e0a04339 · inbound

Sustainable Hybrid Document-Routed Retrieval for Financial RAG: Resolving the Robustness-Precision Trade-off cites this paper.

Sustainable Hybrid Document-Routed Retrieval for Financial RAG: Resolving the Robustness-Precision Trade-off Improving Text Embeddings with Large Language Models

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T00:23:22.811982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c4e15c47-bc6b-4b55-8fa7-b73285cc96e3 · inbound

Regime-Conditional Retrieval: Theory and a Transferable Router for Two-Hop QA cites this paper.

Regime-Conditional Retrieval: Theory and a Transferable Router for Two-Hop QA Improving Text Embeddings with Large Language Models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:15:59.448865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 33a362a8-da07-49fc-8c04-e450457da88b · inbound

IntrAgent: An LLM Agent for Content-Grounded Information Retrieval through Literature Review cites this paper.

IntrAgent: An LLM Agent for Content-Grounded Information Retrieval through Literature Review Improving Text Embeddings with Large Language Models

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T14:41:13.035102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1fd2a61f-40b1-46a2-8055-06aab6e539f8 · inbound

Is Textual Similarity Invariant under Machine Translation? Evidence Based on the Political Manifesto Corpus cites this paper.

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:41:22.076272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 80c6611d-5a1c-41c0-9f81-b91cbaf12eba · inbound

Test-Time Compute for Frozen Embedding Models through Agentic Program Search cites this paper.

Test-Time Compute for Frozen Embedding Models through Agentic Program Search Improving Text Embeddings with Large Language Models

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:15:46.567301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2aa5624b-adbe-4272-b805-9c090832a80b · inbound

MathAtlas: A Benchmark for Autoformalization in the Wild cites this paper.

MathAtlas: A Benchmark for Autoformalization in the Wild Improving Text Embeddings with Large Language Models

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:09:44.416792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e3a8e3d6-0113-4512-a5b5-0914c87eac6c · inbound

Not All RAGs Are Created Equal: A Component-Wise Empirical Study for Software Engineering Tasks cites this paper.

Not All RAGs Are Created Equal: A Component-Wise Empirical Study for Software Engineering Tasks Improving Text Embeddings with Large Language Models

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-15T01:53:28.533543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 33354ea9-4532-43a3-839d-8f8a0050dce8 · inbound

Semantic Reranking at Inference Time for Hard Examples in Rhetorical Role Labeling cites this paper.

Semantic Reranking at Inference Time for Hard Examples in Rhetorical Role Labeling Improving Text Embeddings with Large Language Models

Reference 98

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T11:28:14.317260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4460fd27-484b-43e4-ad0b-47c8d770aafe · inbound

Fine-grained Claim-level RAG Benchmark for Law cites this paper.

Fine-grained Claim-level RAG Benchmark for Law Improving Text Embeddings with Large Language Models

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:13:58.067890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 06f46187-a59b-488b-8d1b-a4cc0e107909 · inbound

Fine-grained Claim-level RAG Benchmark for Law cites this paper.

Fine-grained Claim-level RAG Benchmark for Law Improving Text Embeddings with Large Language Models

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-22T09:44:45.790269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e8b226f2-4465-416a-a9ad-026fda73c734 · inbound

Fine-grained Claim-level RAG Benchmark for Law cites this paper.

Fine-grained Claim-level RAG Benchmark for Law Improving Text Embeddings with Large Language Models

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:55:22.902744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 21673b14-8f3d-4975-883c-a6bfcf8ead27 · inbound

Structure Retention in Embedding Spaces as a Predictor of Benchmark Performance cites this paper.

Structure Retention in Embedding Spaces as a Predictor of Benchmark Performance Improving Text Embeddings with Large Language Models

Reference 130

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:24:40.812675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4a5852b5-25e5-4ef4-a099-cb41e7a9b942 · inbound

Semantic Retrieval for Product Search in E-Commerce cites this paper.

Semantic Retrieval for Product Search in E-Commerce Improving Text Embeddings with Large Language Models

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T21:56:15.922664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a170a590-d78f-40da-b0c0-50be1e31b483 · inbound

LaME: Learning to Think in Latent Space for Multimodal Embedding via Information Bottleneck cites this paper.

LaME: Learning to Think in Latent Space for Multimodal Embedding via Information Bottleneck Improving Text Embeddings with Large Language Models

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T13:48:21.004625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 41311a29-cbab-479f-a8a7-d5ad035ccadf · inbound

Learning to Reason by Analogy via Retrieval-Augmented Reinforcement Fine-Tuning cites this paper.

Learning to Reason by Analogy via Retrieval-Augmented Reinforcement Fine-Tuning Improving Text Embeddings with Large Language Models

Reference 51

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T15:28:33.927072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f83c0eca-e45a-4ad6-bd34-42419c7d9498 · inbound

Improving Long-Context Retrieval with Multi-Prefix Embedding cites this paper.

Improving Long-Context Retrieval with Multi-Prefix Embedding Improving Text Embeddings with Large Language Models

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T12:39:49.191585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 203d6319-0b20-48dc-8fb5-c7e3b4f9b444 · inbound

One Generator, Any Process: LLM-Conditioning for the LHC cites this paper.

One Generator, Any Process: LLM-Conditioning for the LHC Improving Text Embeddings with Large Language Models

Reference 239

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T11:39:46.477494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a5aa57e3-94c4-4e95-a743-9cc8298b160f · inbound

One Generator, Any Process: LLM-Conditioning for the LHC cites this paper.

One Generator, Any Process: LLM-Conditioning for the LHC Improving Text Embeddings with Large Language Models

Reference 243

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T10:14:36.174072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ab88ef6c-f3a2-4824-83d2-3a555684c372 · inbound

Universal Guideline-Driven Image Clustering via a Hybrid LLM Agent cites this paper.

Universal Guideline-Driven Image Clustering via a Hybrid LLM Agent Improving Text Embeddings with Large Language Models

Reference 80

Resolution: verified exact; arxiv_id, observed 2026-07-04T15:49:57.637916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1c64b6af-b1da-48d4-bf2a-3b1e5eabd7a6 · inbound

Bifrost: Empowering Pretrained Language Model with Fallibility Representation for Log-Based Fault Diagnosis cites this paper.

Bifrost: Empowering Pretrained Language Model with Fallibility Representation for Log-Based Fault Diagnosis Improving Text Embeddings with Large Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-01T03:29:59.706111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26b078ce-94c2-41f7-9b48-d2e99247b172 · inbound

Exploring Block Anomaly Detection In HDFS Log Data Analysis cites this paper.

Exploring Block Anomaly Detection In HDFS Log Data Analysis Improving Text Embeddings with Large Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-03T08:06:41.215490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 550e170d-c590-49c9-ab64-5dfa8ab8750d · inbound

UEmbed: Unified Sparse and Dense Multimodal Embeddings cites this paper.

UEmbed: Unified Sparse and Dense Multimodal Embeddings Improving Text Embeddings with Large Language Models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-04T04:19:07.893305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers