Transformers

Applied to New Tool: the Residual Stream Viewer by Adam Yedidia 2mo ago

Applied to World, mind, and learnability: A note on the metaphysical structure of the cosmos [& LLMs] by Bill Benzon 3mo ago

Applied to Google DeepMind's RT-2 by SandXbox 4mo ago

Applied to The positional embedding matrix and previous-token heads: how do they actually work? by Adam Yedidia 4mo ago

Applied to How LLMs are and are not myopic by janus 4mo ago

Applied to GPT-2's positional embedding matrix is a helix by Adam Yedidia 4mo ago

Applied to Killing Recurrent Memory Over Self Attention? by Del Nobolo 6mo ago

Applied to Neuroevolution, Social Intelligence, and Logic by vinnik.dmitry07 6mo ago

Applied to Transformer Architecture Choice for Resisting Prompt Injection and Jail-Breaking Attacks by Roger Dearnaley 6mo ago

Applied to An Analogy for Understanding Transformers by CallumMcDougall 7mo ago

Applied to Residual stream norms grow exponentially over the forward pass by Alex Turner 7mo ago

Applied to We Need To Know About Continual Learning by michael_mjd 7mo ago

Applied to So, just why do GPTs have to operate by continuing an existing string? by Bill Benzon 8mo ago

Applied to How Do Induction Heads Actually Work in Transformers With Finite Capacity? by Ruben Bloom 8mo ago

Applied to Google's PaLM-E: An Embodied Multimodal Language Model by Kaj Sotala 9mo ago

Applied to Addendum: More Efficient FFNs via Attention by Robert_AIZI 10mo ago

Applied to No Really, Attention is ALL You Need - Attention can do feedforward networks by Robert_AIZI 10mo ago

Applied to Tracr: Compiled Transformers as a Laboratory for Interpretability | DeepMind by Cinera Verinia 1y ago

Applied to Are Mixture-of-Experts Transformers More Interpretable Than Dense Transformers? by simeon_c 1y ago