Collections
Discover the best community collections!
Collections including paper arxiv:2309.03409
-
Robotic Table Tennis: A Case Study into a High Speed Learning System
Paper • 2309.03315 • Published • 7 -
FLM-101B: An Open LLM and How to Train It with $100K Budget
Paper • 2309.03852 • Published • 44 -
GPT Can Solve Mathematical Problems Without a Calculator
Paper • 2309.03241 • Published • 18 -
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 77
-
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 77 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 107 -
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework
Paper • 2404.14619 • Published • 126 -
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Paper • 2404.14219 • Published • 259
-
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 77 -
One Wide Feedforward is All You Need
Paper • 2309.01826 • Published • 33 -
Self-Alignment with Instruction Backtranslation
Paper • 2308.06259 • Published • 42 -
Shepherd: A Critic for Language Model Generation
Paper • 2308.04592 • Published • 32
-
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 77 -
Challenges and Applications of Large Language Models
Paper • 2307.10169 • Published • 49 -
Efficiently Modeling Long Sequences with Structured State Spaces
Paper • 2111.00396 • Published • 3 -
DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning
Paper • 2006.08381 • Published
-
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 77 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 107 -
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework
Paper • 2404.14619 • Published • 126 -
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Paper • 2404.14219 • Published • 259
-
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 77 -
One Wide Feedforward is All You Need
Paper • 2309.01826 • Published • 33 -
Self-Alignment with Instruction Backtranslation
Paper • 2308.06259 • Published • 42 -
Shepherd: A Critic for Language Model Generation
Paper • 2308.04592 • Published • 32
-
Robotic Table Tennis: A Case Study into a High Speed Learning System
Paper • 2309.03315 • Published • 7 -
FLM-101B: An Open LLM and How to Train It with $100K Budget
Paper • 2309.03852 • Published • 44 -
GPT Can Solve Mathematical Problems Without a Calculator
Paper • 2309.03241 • Published • 18 -
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 77
-
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 77 -
Challenges and Applications of Large Language Models
Paper • 2307.10169 • Published • 49 -
Efficiently Modeling Long Sequences with Structured State Spaces
Paper • 2111.00396 • Published • 3 -
DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning
Paper • 2006.08381 • Published