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Dissecting In-Context Learning of Translations in GPTs
Paper β’ 2310.15987 β’ Published β’ 6 -
In-Context Learning Creates Task Vectors
Paper β’ 2310.15916 β’ Published β’ 43 -
ZeroGen: Efficient Zero-shot Learning via Dataset Generation
Paper β’ 2202.07922 β’ Published β’ 1 -
Promptor: A Conversational and Autonomous Prompt Generation Agent for Intelligent Text Entry Techniques
Paper β’ 2310.08101 β’ Published β’ 2
Collections
Discover the best community collections!
Collections trending this week
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Woodpecker: Hallucination Correction for Multimodal Large Language Models
Paper β’ 2310.16045 β’ Published β’ 18 -
HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models
Paper β’ 2310.14566 β’ Published β’ 27 -
SILC: Improving Vision Language Pretraining with Self-Distillation
Paper β’ 2310.13355 β’ Published β’ 9 -
Conditional Diffusion Distillation
Paper β’ 2310.01407 β’ Published β’ 19
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Woodpecker: Hallucination Correction for Multimodal Large Language Models
Paper β’ 2310.16045 β’ Published β’ 18 -
HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models
Paper β’ 2310.14566 β’ Published β’ 27 -
MAF: Multi-Aspect Feedback for Improving Reasoning in Large Language Models
Paper β’ 2310.12426 β’ Published β’ 1 -
Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration
Paper β’ 2310.00280 β’ Published β’ 3
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Dissecting In-Context Learning of Translations in GPTs
Paper β’ 2310.15987 β’ Published β’ 6 -
In-Context Learning Creates Task Vectors
Paper β’ 2310.15916 β’ Published β’ 43 -
ZeroGen: Efficient Zero-shot Learning via Dataset Generation
Paper β’ 2202.07922 β’ Published β’ 1 -
Promptor: A Conversational and Autonomous Prompt Generation Agent for Intelligent Text Entry Techniques
Paper β’ 2310.08101 β’ Published β’ 2
-
Woodpecker: Hallucination Correction for Multimodal Large Language Models
Paper β’ 2310.16045 β’ Published β’ 18 -
HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models
Paper β’ 2310.14566 β’ Published β’ 27 -
MAF: Multi-Aspect Feedback for Improving Reasoning in Large Language Models
Paper β’ 2310.12426 β’ Published β’ 1 -
Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration
Paper β’ 2310.00280 β’ Published β’ 3
-
Woodpecker: Hallucination Correction for Multimodal Large Language Models
Paper β’ 2310.16045 β’ Published β’ 18 -
HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models
Paper β’ 2310.14566 β’ Published β’ 27 -
SILC: Improving Vision Language Pretraining with Self-Distillation
Paper β’ 2310.13355 β’ Published β’ 9 -
Conditional Diffusion Distillation
Paper β’ 2310.01407 β’ Published β’ 19