-
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:2403.18802
-
Long-form factuality in large language models
Paper • 2403.18802 • Published • 26 -
Attention Is All You Need
Paper • 1706.03762 • Published • 96 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 17 -
A Survey of GPT-3 Family Large Language Models Including ChatGPT and GPT-4
Paper • 2310.12321 • Published • 1
-
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Paper • 2403.12968 • Published • 25 -
PERL: Parameter Efficient Reinforcement Learning from Human Feedback
Paper • 2403.10704 • Published • 59 -
Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations
Paper • 2403.09704 • Published • 33 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 72
-
BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text
Paper • 2403.18421 • Published • 23 -
Long-form factuality in large language models
Paper • 2403.18802 • Published • 26 -
stanford-crfm/BioMedLM
Text Generation • Updated • 2.58k • 441 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 63
-
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
-
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Paper • 2403.12968 • Published • 25 -
PERL: Parameter Efficient Reinforcement Learning from Human Feedback
Paper • 2403.10704 • Published • 59 -
Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations
Paper • 2403.09704 • Published • 33 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 72
-
Long-form factuality in large language models
Paper • 2403.18802 • Published • 26 -
Attention Is All You Need
Paper • 1706.03762 • Published • 96 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 17 -
A Survey of GPT-3 Family Large Language Models Including ChatGPT and GPT-4
Paper • 2310.12321 • Published • 1
-
BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text
Paper • 2403.18421 • Published • 23 -
Long-form factuality in large language models
Paper • 2403.18802 • Published • 26 -
stanford-crfm/BioMedLM
Text Generation • Updated • 2.58k • 441 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 63