1.2k citations · 2.4k across the 13 of their papers we have counts for
4 papers · 1 filter
Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs
Kelvin Guu, Albert Webson, Ellie Pavlick +3
Training data attribution (TDA) methods offer to trace a model's prediction on any given example back to specific influential training examples. Existing approaches do so by assign…
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…
The Flan Collection: Designing Data and Methods for Effective Instruction Tuning
Shayne Longpre, Le Hou, Tu Vu +8
We study the design decisions of publicly available instruction tuning methods, and break down the development of Flan 2022 (Chung et al., 2022). Through careful ablation studies o…
Are Language Models Worse than Humans at Following Prompts? It's Complicated
Albert Webson, Alyssa Marie Loo, Qinan Yu +1
Prompts have been the center of progress in advancing language models' zero-shot and few-shot performance. However, recent work finds that models can perform surprisingly well when…