- 
	
	
	
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 • 23 - 
	
	
	
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:2009.03300 
						
					
				- 
	
	
	
Measuring Massive Multitask Language Understanding
Paper • 2009.03300 • Published • 3 - 
	
	
	
MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark
Paper • 2406.01574 • Published • 51 - 
	
	
	
GPQA: A Graduate-Level Google-Proof Q&A Benchmark
Paper • 2311.12022 • Published • 33 - 
	
	
	
HellaSwag: Can a Machine Really Finish Your Sentence?
Paper • 1905.07830 • Published • 6 
- 
	
	
	
RARR: Researching and Revising What Language Models Say, Using Language Models
Paper • 2210.08726 • Published • 1 - 
	
	
	
Hypothesis Search: Inductive Reasoning with Language Models
Paper • 2309.05660 • Published • 2 - 
	
	
	
In-context Learning and Induction Heads
Paper • 2209.11895 • Published • 2 - 
	
	
	
ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 30 
- 
	
	
	
Gemini: A Family of Highly Capable Multimodal Models
Paper • 2312.11805 • Published • 47 - 
	
	
	
Measuring Massive Multitask Language Understanding
Paper • 2009.03300 • Published • 3 - 
	
	
	
HellaSwag: Can a Machine Really Finish Your Sentence?
Paper • 1905.07830 • Published • 6 - 
	
	
	
PIQA: Reasoning about Physical Commonsense in Natural Language
Paper • 1911.11641 • Published • 3 
- 
	
	
	
Humanity's Last Exam
Paper • 2501.14249 • Published • 76 - 
	
	
	
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Paper • 2206.04615 • Published • 5 - 
	
	
	
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
Paper • 2210.09261 • Published • 1 - 
	
	
	
BIG-Bench Extra Hard
Paper • 2502.19187 • Published • 10 
- 
	
	
	
Re3: Generating Longer Stories With Recursive Reprompting and Revision
Paper • 2210.06774 • Published • 2 - 
	
	
	
Constitutional AI: Harmlessness from AI Feedback
Paper • 2212.08073 • Published • 3 - 
	
	
	
AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls
Paper • 2402.04253 • Published - 
	
	
	
Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate
Paper • 2305.19118 • Published 
- 
	
	
	
Attention Is All You Need
Paper • 1706.03762 • Published • 94 - 
	
	
	
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 23 - 
	
	
	
Universal Language Model Fine-tuning for Text Classification
Paper • 1801.06146 • Published • 7 - 
	
	
	
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 17 
- 
	
	
	
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 • 23 - 
	
	
	
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 
- 
	
	
	
Humanity's Last Exam
Paper • 2501.14249 • Published • 76 - 
	
	
	
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Paper • 2206.04615 • Published • 5 - 
	
	
	
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
Paper • 2210.09261 • Published • 1 - 
	
	
	
BIG-Bench Extra Hard
Paper • 2502.19187 • Published • 10 
- 
	
	
	
Measuring Massive Multitask Language Understanding
Paper • 2009.03300 • Published • 3 - 
	
	
	
MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark
Paper • 2406.01574 • Published • 51 - 
	
	
	
GPQA: A Graduate-Level Google-Proof Q&A Benchmark
Paper • 2311.12022 • Published • 33 - 
	
	
	
HellaSwag: Can a Machine Really Finish Your Sentence?
Paper • 1905.07830 • Published • 6 
- 
	
	
	
RARR: Researching and Revising What Language Models Say, Using Language Models
Paper • 2210.08726 • Published • 1 - 
	
	
	
Hypothesis Search: Inductive Reasoning with Language Models
Paper • 2309.05660 • Published • 2 - 
	
	
	
In-context Learning and Induction Heads
Paper • 2209.11895 • Published • 2 - 
	
	
	
ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 30 
- 
	
	
	
Re3: Generating Longer Stories With Recursive Reprompting and Revision
Paper • 2210.06774 • Published • 2 - 
	
	
	
Constitutional AI: Harmlessness from AI Feedback
Paper • 2212.08073 • Published • 3 - 
	
	
	
AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls
Paper • 2402.04253 • Published - 
	
	
	
Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate
Paper • 2305.19118 • Published 
- 
	
	
	
Gemini: A Family of Highly Capable Multimodal Models
Paper • 2312.11805 • Published • 47 - 
	
	
	
Measuring Massive Multitask Language Understanding
Paper • 2009.03300 • Published • 3 - 
	
	
	
HellaSwag: Can a Machine Really Finish Your Sentence?
Paper • 1905.07830 • Published • 6 - 
	
	
	
PIQA: Reasoning about Physical Commonsense in Natural Language
Paper • 1911.11641 • Published • 3 
- 
	
	
	
Attention Is All You Need
Paper • 1706.03762 • Published • 94 - 
	
	
	
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 23 - 
	
	
	
Universal Language Model Fine-tuning for Text Classification
Paper • 1801.06146 • Published • 7 - 
	
	
	
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 17