1.3k citations · 3.7k across the 43 of their papers we have counts for
8 papers · 1 filter
The Temporal Structure of Language Processing in the Human Brain Corresponds to The Layered Hierarchy of Deep Language Models
Ariel Goldstein, Eric Ham, Mariano Schain +17
Deep Language Models (DLMs) provide a novel computational paradigm for understanding the mechanisms of natural language processing in the human brain. Unlike traditional psycholing…
Self-Alignment with Instruction Backtranslation
Xian Li, Ping Yu, Chunting Zhou +5
We present a scalable method to build a high quality instruction following language model by automatically labelling human-written text with corresponding instructions. Our approac…
LIMA: Less Is More for Alignment
Chunting Zhou, Pengfei Liu, Puxin Xu +12
Large language models are trained in two stages: (1) unsupervised pretraining from raw text, to learn general-purpose representations, and (2) large scale instruction tuning and re…
ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding
Uri Shaham, Maor Ivgi, Avia Efrat +2
We introduce ZeroSCROLLS, a zero-shot benchmark for natural language understanding over long texts, which contains only test and small validation sets, without training data. We ad…
Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation
Yuval Kirstain, Adam Polyak, Uriel Singer +3
The ability to collect a large dataset of human preferences from text-to-image users is usually limited to companies, making such datasets inaccessible to the public. To address th…
Vision Transformers with Mixed-Resolution Tokenization
Tomer Ronen, Omer Levy, Avram Golbert
Vision Transformer models process input images by dividing them into a spatially regular grid of equal-size patches. Conversely, Transformers were originally introduced over natura…