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Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning
Paper • 2211.04325 • Published • 1 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 24 -
On the Opportunities and Risks of Foundation Models
Paper • 2108.07258 • Published • 1 -
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 2
Collections
Discover the best community collections!
Collections including paper arxiv:2307.03109
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Instruction-Following Evaluation for Large Language Models
Paper • 2311.07911 • Published • 22 -
HuggingFaceH4/mt_bench_prompts
Viewer • Updated • 80 • 3.44k • 21 -
vectara/hallucination_evaluation_model
Text Classification • 0.1B • Updated • 101k • 336 -
GAIA: a benchmark for General AI Assistants
Paper • 2311.12983 • Published • 241
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Attention Is All You Need
Paper • 1706.03762 • Published • 105 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 18 -
Learning to summarize from human feedback
Paper • 2009.01325 • Published • 4 -
Training language models to follow instructions with human feedback
Paper • 2203.02155 • Published • 24
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A Survey on Evaluation of Large Language Models
Paper • 2307.03109 • Published • 42 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25 -
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
Paper • 2402.10524 • Published • 23
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Levels of AGI for Operationalizing Progress on the Path to AGI
Paper • 2311.02462 • Published • 38 -
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Paper • 2206.04615 • Published • 5 -
A Survey on Evaluation of Large Language Models
Paper • 2307.03109 • Published • 42 -
Bring Your Own Data! Self-Supervised Evaluation for Large Language Models
Paper • 2306.13651 • Published • 15
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Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning
Paper • 2211.04325 • Published • 1 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 24 -
On the Opportunities and Risks of Foundation Models
Paper • 2108.07258 • Published • 1 -
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 2
-
A Survey on Evaluation of Large Language Models
Paper • 2307.03109 • Published • 42 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25 -
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
Paper • 2402.10524 • Published • 23
-
Instruction-Following Evaluation for Large Language Models
Paper • 2311.07911 • Published • 22 -
HuggingFaceH4/mt_bench_prompts
Viewer • Updated • 80 • 3.44k • 21 -
vectara/hallucination_evaluation_model
Text Classification • 0.1B • Updated • 101k • 336 -
GAIA: a benchmark for General AI Assistants
Paper • 2311.12983 • Published • 241
-
Levels of AGI for Operationalizing Progress on the Path to AGI
Paper • 2311.02462 • Published • 38 -
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Paper • 2206.04615 • Published • 5 -
A Survey on Evaluation of Large Language Models
Paper • 2307.03109 • Published • 42 -
Bring Your Own Data! Self-Supervised Evaluation for Large Language Models
Paper • 2306.13651 • Published • 15
-
Attention Is All You Need
Paper • 1706.03762 • Published • 105 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 18 -
Learning to summarize from human feedback
Paper • 2009.01325 • Published • 4 -
Training language models to follow instructions with human feedback
Paper • 2203.02155 • Published • 24