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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:2410.07073
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Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 119 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 142
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Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages
Paper • 2410.16153 • Published • 44 -
AutoTrain: No-code training for state-of-the-art models
Paper • 2410.15735 • Published • 59 -
The Curse of Multi-Modalities: Evaluating Hallucinations of Large Multimodal Models across Language, Visual, and Audio
Paper • 2410.12787 • Published • 31 -
LEOPARD : A Vision Language Model For Text-Rich Multi-Image Tasks
Paper • 2410.01744 • Published • 26
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GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Paper • 2403.03507 • Published • 189 -
Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Models
Paper • 2407.01906 • Published • 45 -
QLoRA: Efficient Finetuning of Quantized LLMs
Paper • 2305.14314 • Published • 57 -
LoRA+: Efficient Low Rank Adaptation of Large Models
Paper • 2402.12354 • Published • 7
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Flowing from Words to Pixels: A Framework for Cross-Modality Evolution
Paper • 2412.15213 • Published • 28 -
No More Adam: Learning Rate Scaling at Initialization is All You Need
Paper • 2412.11768 • Published • 43 -
Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
Paper • 2412.13663 • Published • 158 -
Autoregressive Video Generation without Vector Quantization
Paper • 2412.14169 • Published • 14
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NVLM: Open Frontier-Class Multimodal LLMs
Paper • 2409.11402 • Published • 74 -
BRAVE: Broadening the visual encoding of vision-language models
Paper • 2404.07204 • Published • 19 -
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
Paper • 2403.18814 • Published • 47 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121
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Qwen2.5 Technical Report
Paper • 2412.15115 • Published • 376 -
Qwen2.5-Coder Technical Report
Paper • 2409.12186 • Published • 151 -
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
Paper • 2409.12122 • Published • 4 -
Qwen2.5-VL Technical Report
Paper • 2502.13923 • Published • 211
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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
-
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Paper • 2403.03507 • Published • 189 -
Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Models
Paper • 2407.01906 • Published • 45 -
QLoRA: Efficient Finetuning of Quantized LLMs
Paper • 2305.14314 • Published • 57 -
LoRA+: Efficient Low Rank Adaptation of Large Models
Paper • 2402.12354 • Published • 7
-
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 119 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 142
-
Flowing from Words to Pixels: A Framework for Cross-Modality Evolution
Paper • 2412.15213 • Published • 28 -
No More Adam: Learning Rate Scaling at Initialization is All You Need
Paper • 2412.11768 • Published • 43 -
Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
Paper • 2412.13663 • Published • 158 -
Autoregressive Video Generation without Vector Quantization
Paper • 2412.14169 • Published • 14
-
NVLM: Open Frontier-Class Multimodal LLMs
Paper • 2409.11402 • Published • 74 -
BRAVE: Broadening the visual encoding of vision-language models
Paper • 2404.07204 • Published • 19 -
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
Paper • 2403.18814 • Published • 47 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121
-
Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages
Paper • 2410.16153 • Published • 44 -
AutoTrain: No-code training for state-of-the-art models
Paper • 2410.15735 • Published • 59 -
The Curse of Multi-Modalities: Evaluating Hallucinations of Large Multimodal Models across Language, Visual, and Audio
Paper • 2410.12787 • Published • 31 -
LEOPARD : A Vision Language Model For Text-Rich Multi-Image Tasks
Paper • 2410.01744 • Published • 26
-
Qwen2.5 Technical Report
Paper • 2412.15115 • Published • 376 -
Qwen2.5-Coder Technical Report
Paper • 2409.12186 • Published • 151 -
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
Paper • 2409.12122 • Published • 4 -
Qwen2.5-VL Technical Report
Paper • 2502.13923 • Published • 211