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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2408.02545
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RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generation
Paper • 2408.02545 • Published • 39 -
RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering
Paper • 2407.13998 • Published -
RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation
Paper • 2408.08067 • Published • 1 -
RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning
Paper • 2504.20073 • Published • 12
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RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generation
Paper • 2408.02545 • Published • 39 -
HyperCLOVA X THINK Technical Report
Paper • 2506.22403 • Published -
HyperCLOVA X Technical Report
Paper • 2404.01954 • Published • 25 -
KMMLU: Measuring Massive Multitask Language Understanding in Korean
Paper • 2402.11548 • Published
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Enhanced Multimodal RAG-LLM for Accurate Visual Question Answering
Paper • 2412.20927 • Published • 1 -
BioRAG: A RAG-LLM Framework for Biological Question Reasoning
Paper • 2408.01107 • Published -
Developing Retrieval Augmented Generation (RAG) based LLM Systems from PDFs: An Experience Report
Paper • 2410.15944 • Published -
Tuning LLMs by RAG Principles: Towards LLM-native Memory
Paper • 2503.16071 • Published
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LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 34 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 27 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 126 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 22
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RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generation
Paper • 2408.02545 • Published • 39 -
BERGEN: A Benchmarking Library for Retrieval-Augmented Generation
Paper • 2407.01102 • Published -
UniversalRAG: Retrieval-Augmented Generation over Multiple Corpora with Diverse Modalities and Granularities
Paper • 2504.20734 • Published • 61 -
VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents
Paper • 2410.10594 • Published • 28
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 34 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 27 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 126 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 22
-
RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generation
Paper • 2408.02545 • Published • 39 -
RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering
Paper • 2407.13998 • Published -
RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation
Paper • 2408.08067 • Published • 1 -
RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning
Paper • 2504.20073 • Published • 12
-
RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generation
Paper • 2408.02545 • Published • 39 -
HyperCLOVA X THINK Technical Report
Paper • 2506.22403 • Published -
HyperCLOVA X Technical Report
Paper • 2404.01954 • Published • 25 -
KMMLU: Measuring Massive Multitask Language Understanding in Korean
Paper • 2402.11548 • Published
-
RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generation
Paper • 2408.02545 • Published • 39 -
BERGEN: A Benchmarking Library for Retrieval-Augmented Generation
Paper • 2407.01102 • Published -
UniversalRAG: Retrieval-Augmented Generation over Multiple Corpora with Diverse Modalities and Granularities
Paper • 2504.20734 • Published • 61 -
VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents
Paper • 2410.10594 • Published • 28
-
Enhanced Multimodal RAG-LLM for Accurate Visual Question Answering
Paper • 2412.20927 • Published • 1 -
BioRAG: A RAG-LLM Framework for Biological Question Reasoning
Paper • 2408.01107 • Published -
Developing Retrieval Augmented Generation (RAG) based LLM Systems from PDFs: An Experience Report
Paper • 2410.15944 • Published -
Tuning LLMs by RAG Principles: Towards LLM-native Memory
Paper • 2503.16071 • Published