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An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models
Paper • 2309.09958 • Published • 18 -
TextBind: Multi-turn Interleaved Multimodal Instruction-following
Paper • 2309.08637 • Published • 7 -
AnyMAL: An Efficient and Scalable Any-Modality Augmented Language Model
Paper • 2309.16058 • Published • 55 -
Qwen Technical Report
Paper • 2309.16609 • Published • 34
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Collections including paper arxiv:2309.09958
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Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Paper • 2309.08532 • Published • 52 -
A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale
Paper • 2309.06497 • Published • 4 -
MindAgent: Emergent Gaming Interaction
Paper • 2309.09971 • Published • 11 -
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages
Paper • 2309.09400 • Published • 82
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DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
Paper • 2309.03883 • Published • 33 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 30 -
Agents: An Open-source Framework for Autonomous Language Agents
Paper • 2309.07870 • Published • 41 -
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Paper • 2309.00267 • Published • 47