Revisiting the Superficial Alignment Hypothesis

27 September 2024

Papers citing "Revisiting the Superficial Alignment Hypothesis"

8 / 8 papers shown

Title
Large Language Monkeys: Scaling Inference Compute with Repeated Sampling Bradley Brown Jordan Juravsky Ryan Ehrlich Ronald Clark Quoc V. Le Christopher Ré Azalia Mirhoseini ALM LRM 209 292 0 03 Jan 2025
Is In-Context Learning Sufficient for Instruction Following in LLMs? Hao Zhao Maksym Andriushchenko Francesco Croce Nicolas Flammarion 82 14 0 30 May 2024
GPT-4 Technical Report OpenAI OpenAI OpenAI Josh Achiam Steven Adler Sandhini Agarwal Lama Ahmad ... Shengjia Zhao Tianhao Zheng Juntang Zhuang William Zhuk Barret Zoph LLMAG MLLM 996 14,179 0 15 Mar 2023
Training Compute-Optimal Large Language Models Jordan Hoffmann Sebastian Borgeaud A. Mensch Elena Buchatskaya Trevor Cai ... Karen Simonyan Erich Elsen Jack W. Rae Oriol Vinyals Laurent Sifre AI4TS 180 1,936 0 29 Mar 2022
Finetuned Language Models Are Zero-Shot Learners Jason W. Wei Maarten Bosma Vincent Zhao Kelvin Guu Adams Wei Yu Brian Lester Nan Du Andrew M. Dai Quoc V. Le ALM UQCV 114 3,723 0 03 Sep 2021
Explaining Neural Scaling Laws Yasaman Bahri Ethan Dyer Jared Kaplan Jaehoon Lee Utkarsh Sharma 54 260 0 12 Feb 2021
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 594 41,736 0 28 May 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 520 4,773 0 23 Jan 2020