Machine Learning Research
A 3D Mesh From One 2D Image: The combination of video diffusion and Neural Radiance Field (NeRF) can produce a 3D mesh from a single image
Video diffusion provides a new basis for generating 3D models.
Machine Learning Research
Video diffusion provides a new basis for generating 3D models.
Machine Learning Research
Retrieval-augmented generation (RAG) enables large language models to generate better output by retrieving documents that are relevant to a user’s prompt. Fine-tuning further improves RAG performance.
Machine Learning Research
An architectural innovation improves upon transformers — up to 2 billion parameters, at least...
Machine Learning Research
Large language models sometimes generate false statements. New work makes them more likely to produce factual output.
Machine Learning Research
Humanoid robots can play football (known as soccer in the United States) in the real world, thanks to reinforcement learning.
Machine Learning Research
Research aims to help users select large language models that minimize expenses while maintaining quality.
Machine Learning Research
Robots equipped with large language models are asking their human overseers for help.
Machine Learning Research
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
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
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.
Tech & Society
Google asserted its open source bona fides with new models. Google released weights for Gemma-7B, an 8.5 billion-parameter large language model intended to run GPUs, and Gemma-2B, a 2.5 billion-parameter version intended for deployment on CPUs and edge devices.
Machine Learning Research
Reinforcement learning from human feedback (RLHF) is widely used to fine-tune pretrained models to deliver outputs that align with human preferences. New work aligns pretrained models without the cumbersome step of reinforcement learning.