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Improving Text Embeddings with Large Language Models
Paper • 2401.00368 • Published • 77 -
Piccolo2: General Text Embedding with Multi-task Hybrid Loss Training
Paper • 2405.06932 • Published • 15 -
Gecko: Versatile Text Embeddings Distilled from Large Language Models
Paper • 2403.20327 • Published • 47 -
Multilingual E5 Text Embeddings: A Technical Report
Paper • 2402.05672 • Published • 16
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Collections including paper arxiv:2401.00368
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Text Embeddings by Weakly-Supervised Contrastive Pre-training
Paper • 2212.03533 • Published • 1 -
Gecko: Versatile Text Embeddings Distilled from Large Language Models
Paper • 2403.20327 • Published • 47 -
Improving Text Embeddings with Large Language Models
Paper • 2401.00368 • Published • 77 -
Generative Representational Instruction Tuning
Paper • 2402.09906 • Published • 50
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 573 -
Atom: Low-bit Quantization for Efficient and Accurate LLM Serving
Paper • 2310.19102 • Published • 7 -
AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning
Paper • 2311.00257 • Published • 8 -
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 48
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Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 91 -
How to Train Data-Efficient LLMs
Paper • 2402.09668 • Published • 34 -
BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 17 -
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts
Paper • 2402.09727 • Published • 35
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World Model on Million-Length Video And Language With RingAttention
Paper • 2402.08268 • Published • 35 -
Improving Text Embeddings with Large Language Models
Paper • 2401.00368 • Published • 77 -
Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 91 -
FiT: Flexible Vision Transformer for Diffusion Model
Paper • 2402.12376 • Published • 48