Machine Learning Research
A Transformer Alternative Emerges: Mamba, a new approach that may outperform transformers
An architectural innovation improves upon transformers — up to 2 billion parameters, at least...
Machine Learning Research
More Factual LLMs: FactTune, a method to fine-tune LLMs for factual accuracy without human feedback
Large language models sometimes generate false statements. New work makes them more likely to produce factual output.
Machine Learning Research
More Factual LLMs: FactTune, a method to fine-tune LLMs for factual accuracy without human feedback
Large language models sometimes generate false statements. New work makes them more likely to produce factual output.
Machine Learning Research
Robo-Football From Simulation to Reality: Reinforcement learning powers humanoid robots to play football
Humanoid robots can play football (known as soccer in the United States) in the real world, thanks to reinforcement learning.
Machine Learning Research
Robo-Football From Simulation to Reality: Reinforcement learning powers humanoid robots to play football
Humanoid robots can play football (known as soccer in the United States) in the real world, thanks to reinforcement learning.
Machine Learning Research
Cutting the Cost of Pretrained Models: FrugalGPT, a method to cut AI costs and maintain quality
Research aims to help users select large language models that minimize expenses while maintaining quality.
Machine Learning Research
Cutting the Cost of Pretrained Models: FrugalGPT, a method to cut AI costs and maintain quality
Research aims to help users select large language models that minimize expenses while maintaining quality.
Machine Learning Research
Conversational Robots: RFM-1, a model that enables robots to understand and act on human commands
Robots equipped with large language models are asking their human overseers for help.
Machine Learning Research
Conversational Robots: RFM-1, a model that enables robots to understand and act on human commands
Robots equipped with large language models are asking their human overseers for help.
Machine Learning Research
Toward Safer, More Helpful Models
The technique known as reinforcement learning from human feedback fine-tunes large language models to be helpful and avoid generating harmful responses such as suggesting illegal or dangerous activities. An alternative method streamlines this approach and achieves better results.
Machine Learning Research
Toward Safer, More Helpful Models
The technique known as reinforcement learning from human feedback fine-tunes large language models to be helpful and avoid generating harmful responses such as suggesting illegal or dangerous activities. An alternative method streamlines this approach and achieves better results.
Machine Learning Research
Learning Language by Exploration: Agent develops language skills through simulated exploration tasks
Machine learning models typically learn language by training on tasks like predicting the next word in a given text. Researchers trained a language model in a less focused, more human-like way.
Machine Learning Research
Learning Language by Exploration: Agent develops language skills through simulated exploration tasks
Machine learning models typically learn language by training on tasks like predicting the next word in a given text. Researchers trained a language model in a less focused, more human-like way.
Machine Learning Research
Schooling Language Models in Math: GOAT (Good at Arithmetic Tasks), a method to boost large language models' arithmetic abilities
Large language models are not good at math. Researchers devised a way to make them better. Tiedong Liu and Bryan Kian Hsiang Low at the National University of Singapore proposed a method to fine-tune large language models for arithmetic tasks.
Machine Learning Research
Schooling Language Models in Math: GOAT (Good at Arithmetic Tasks), a method to boost large language models' arithmetic abilities
Large language models are not good at math. Researchers devised a way to make them better. Tiedong Liu and Bryan Kian Hsiang Low at the National University of Singapore proposed a method to fine-tune large language models for arithmetic tasks.
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