1 code implementation • 24 May 2023 • Harvey Yiyun Fu, Qinyuan Ye, Albert Xu, Xiang Ren, Robin Jia
In this paper, we propose the task of ICL accuracy estimation, in which we predict the accuracy of an LLM when doing in-context learning on a new task given only unlabeled test data for that task.
1 code implementation • 28 Nov 2022 • Albert Xu, Xiang Ren, Robin Jia
In many task settings, text classification models are likely to encounter examples from novel classes on which they cannot predict correctly.
no code implementations • 20 Oct 2022 • Albert Xu, Jhih-Yi Hsieh, Bhaskar Vundurthy, Eliana Cohen, Howie Choset, Lu Li
In this paper, we utilize the mathematical theory of isometric approximation to show an equivalence between the Triplet Loss sampled by hard negative mining and an optimization problem that minimizes a Hausdorff-like distance between the neural network and its ideal counterpart function.
1 code implementation • ACL 2022 • Eric Wallace, Nicholas Tomlin, Albert Xu, Kevin Yang, Eshaan Pathak, Matthew Ginsberg, Dan Klein
We present the Berkeley Crossword Solver, a state-of-the-art approach for automatically solving crossword puzzles.
1 code implementation • NAACL 2021 • Albert Xu, Eshaan Pathak, Eric Wallace, Suchin Gururangan, Maarten Sap, Dan Klein
Language models (LMs) must be both safe and equitable to be responsibly deployed in practice.