168 citations · 326 across the 10 of their papers we have counts for
5 papers · 1 filter
Simple synthetic data reduces sycophancy in large language models
Jerry Wei, Da Huang, Yifeng Lu +2
Sycophancy is an undesirable behavior where models tailor their responses to follow a human user's view even when that view is not objectively correct (e.g., adapting liberal views…
Brainformers: Trading Simplicity for Efficiency
Yanqi Zhou, Nan Du, Yanping Huang +12
Transformers are central to recent successes in natural language processing and computer vision. Transformers have a mostly uniform backbone where layers alternate between feed-for…
Symbol tuning improves in-context learning in language models
Jerry Wei, Le Hou, Andrew Lampinen +8
We present symbol tuning - finetuning language models on in-context input-label pairs where natural language labels (e.g., "positive/negative sentiment") are replaced with arbitrar…
Larger language models do in-context learning differently
Jerry Wei, Jason Wei, Yi Tay +8
We study how in-context learning (ICL) in language models is affected by semantic priors versus input-label mappings. We investigate two setups-ICL with flipped labels and ICL with…
Symbolic Discovery of Optimization Algorithms
Xiangning Chen, Chen Liang, Da Huang +9
We present a method to formulate algorithm discovery as program search, and apply it to discover optimization algorithms for deep neural network training. We leverage efficient sea…