Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models | Paper Citation Record

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BLOOM: A 176B-Parameter Open-Access Multilingual Language Model cites this paper.

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 160

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C-Pack: Packed Resources For General Chinese Embeddings cites this paper.

C-Pack: Packed Resources For General Chinese Embeddings Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 43

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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 Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 37

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

E5-V: Universal Embeddings with Multimodal Large Language Models Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 10

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MVIGER: Multi-View Variational Integration of Complementary Knowledge for Generative Recommender cites this paper.

MVIGER: Multi-View Variational Integration of Complementary Knowledge for Generative Recommender Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 21

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Conjuring Semantic Similarity cites this paper.

Conjuring Semantic Similarity Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 20

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Efficient Alignment of Large Language Models via Data Sampling cites this paper.

Efficient Alignment of Large Language Models via Data Sampling Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 19

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Hiding Communication Cost in Distributed LLM Training via Micro-batch Co-execution cites this paper.

Hiding Communication Cost in Distributed LLM Training via Micro-batch Co-execution Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 34

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Unifying Generative and Dense Retrieval for Sequential Recommendation cites this paper.

Unifying Generative and Dense Retrieval for Sequential Recommendation Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 2022

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Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features cites this paper.

Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 68

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Understanding Bias in Large-Scale Visual Datasets cites this paper.

Understanding Bias in Large-Scale Visual Datasets Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 50

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Large Concept Models: Language Modeling in a Sentence Representation Space cites this paper.

Large Concept Models: Language Modeling in a Sentence Representation Space Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 82

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Owl-1: Omni World Model for Consistent Long Video Generation cites this paper.

Owl-1: Omni World Model for Consistent Long Video Generation Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 22

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FluxSpace: Disentangled Semantic Editing in Rectified Flow Transformers cites this paper.

FluxSpace: Disentangled Semantic Editing in Rectified Flow Transformers Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 28

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Efficient fine-tuning methodology of text embedding models for information retrieval: contrastive learning penalty (clp) cites this paper.

Efficient fine-tuning methodology of text embedding models for information retrieval: contrastive learning penalty (clp) Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 9

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Jasper and Stella: distillation of SOTA embedding models cites this paper.

Jasper and Stella: distillation of SOTA embedding models Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 65

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LUSIFER: Language Universal Space Integration for Enhanced Multilingual Embeddings with Large Language Models cites this paper.

LUSIFER: Language Universal Space Integration for Enhanced Multilingual Embeddings with Large Language Models Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 45

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MoEE: Mixture of Emotion Experts for Audio-Driven Portrait Animation cites this paper.

MoEE: Mixture of Emotion Experts for Audio-Driven Portrait Animation Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 24

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MotionPCM: Real-Time Motion Synthesis with Phased Consistency Model cites this paper.

MotionPCM: Real-Time Motion Synthesis with Phased Consistency Model Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 21

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DOGR: Leveraging Document-Oriented Contrastive Learning in Generative Retrieval cites this paper.

DOGR: Leveraging Document-Oriented Contrastive Learning in Generative Retrieval Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 25

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Bi-Fact: A Bidirectional Factorization-based Evaluation of Intent Extraction from UI Trajectories cites this paper.

Bi-Fact: A Bidirectional Factorization-based Evaluation of Intent Extraction from UI Trajectories Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

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Language Models to Support Multi-Label Classification of Industrial Data cites this paper.

Language Models to Support Multi-Label Classification of Industrial Data Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 25

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Information Leakage of Sentence Embeddings via Generative Embedding Inversion Attacks cites this paper.

Information Leakage of Sentence Embeddings via Generative Embedding Inversion Attacks Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 23

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs cites this paper.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 47

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Intent Classification on Low-Resource Languages with Query Similarity Search cites this paper.

Intent Classification on Low-Resource Languages with Query Similarity Search Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

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Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward cites this paper.

Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 15

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AI Agent Behavioral Science cites this paper.

AI Agent Behavioral Science Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 111

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Output Scaling: YingLong-Delayed Chain of Thought in a Large Pretrained Time Series Forecasting Model cites this paper.

Output Scaling: YingLong-Delayed Chain of Thought in a Large Pretrained Time Series Forecasting Model Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 15

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DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving cites this paper.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 28

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Team LA at SCIDOCA shared task 2025: Citation Discovery via relation-based zero-shot retrieval cites this paper.

Team LA at SCIDOCA shared task 2025: Citation Discovery via relation-based zero-shot retrieval Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

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Act-With-Think: Chunk Auto-Regressive Modeling for Generative Recommendation cites this paper.

Act-With-Think: Chunk Auto-Regressive Modeling for Generative Recommendation Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

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Can Large Language Models Understand As Well As Apply Patent Regulations to Pass a Hands-On Patent Attorney Test? cites this paper.

Can Large Language Models Understand As Well As Apply Patent Regulations to Pass a Hands-On Patent Attorney Test? Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 36

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The Potential Impact of Disruptive AI Innovations on U.S. Occupations cites this paper.

The Potential Impact of Disruptive AI Innovations on U.S. Occupations Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 39

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GRACE: Generative Recommendation via Journey-Aware Sparse Attention on Chain-of-Thought Tokenization cites this paper.

GRACE: Generative Recommendation via Journey-Aware Sparse Attention on Chain-of-Thought Tokenization Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

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HCAttention: Extreme KV Cache Compression via Heterogeneous Attention Computing for LLMs cites this paper.

HCAttention: Extreme KV Cache Compression via Heterogeneous Attention Computing for LLMs Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

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LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points cites this paper.

LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 29

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ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments cites this paper.

ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 51

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CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models cites this paper.

CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 40

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CTA-Flux: Integrating Chinese Cultural Semantics into High-Quality English Text-to-Image Communities cites this paper.

CTA-Flux: Integrating Chinese Cultural Semantics into High-Quality English Text-to-Image Communities Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

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TinyMusician: On-Device Music Generation with Knowledge Distillation and Mixed Precision Quantization cites this paper.

TinyMusician: On-Device Music Generation with Knowledge Distillation and Mixed Precision Quantization Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

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A Survey on Retrieval And Structuring Augmented Generation with Large Language Models cites this paper.

A Survey on Retrieval And Structuring Augmented Generation with Large Language Models Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 180

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Understanding Generative Recommendation with Semantic IDs from a Model-scaling View cites this paper.

Understanding Generative Recommendation with Semantic IDs from a Model-scaling View Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 2019

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Reconstruction-Anchored Diffusion Model for Text-to-Motion Generation cites this paper.

Reconstruction-Anchored Diffusion Model for Text-to-Motion Generation Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

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GenRecEdit: Adapting Model Editing for Generative Recommendation with Cold-Start Items cites this paper.

GenRecEdit: Adapting Model Editing for Generative Recommendation with Cold-Start Items Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 20

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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 Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 31

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Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification cites this paper.

Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 34

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A Comparative Study on Affective Cues in Text Embeddings Across Psychological Emotion Theories cites this paper.

A Comparative Study on Affective Cues in Text Embeddings Across Psychological Emotion Theories Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 36

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Large-Language-Models-as-a-Judge in Theory-Agnostic Adaptive Metric-Alignment for Prototypical Networks in Personality Recognition cites this paper.

Large-Language-Models-as-a-Judge in Theory-Agnostic Adaptive Metric-Alignment for Prototypical Networks in Personality Recognition Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 27

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Choosing a Text Embedding Model: A Practical Benchmarking and Decision Framework cites this paper.

Choosing a Text Embedding Model: A Practical Benchmarking and Decision Framework Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

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GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models cites this paper.

GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 77

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Test-Time Optimization of Query Embeddings with Ranking Aware Reward Maximization cites this paper.

Test-Time Optimization of Query Embeddings with Ranking Aware Reward Maximization Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 47

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