Collections
Discover the best community collections!
Collections including paper arxiv:2310.17750
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Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training
Paper • 2401.05566 • Published • 26 -
On the Societal Impact of Open Foundation Models
Paper • 2403.07918 • Published • 16 -
JudgeLM: Fine-tuned Large Language Models are Scalable Judges
Paper • 2310.17631 • Published • 33 -
Instruction Tuning for Large Language Models: A Survey
Paper • 2308.10792 • Published • 1
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AtP*: An efficient and scalable method for localizing LLM behaviour to components
Paper • 2403.00745 • Published • 11 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 602 -
MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT
Paper • 2402.16840 • Published • 23 -
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Paper • 2402.13753 • Published • 111
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Moral Foundations of Large Language Models
Paper • 2310.15337 • Published • 1 -
Specific versus General Principles for Constitutional AI
Paper • 2310.13798 • Published • 2 -
Contrastive Prefence Learning: Learning from Human Feedback without RL
Paper • 2310.13639 • Published • 24 -
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Paper • 2309.00267 • Published • 47