Papers by Albert Xu
PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts (2022.acl-demo)
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Stephen Bach, Victor Sanh, Zheng Xin Yong, Albert Webson, Colin Raffel, Nihal V. Nayak, Abheesht Sharma, Taewoon Kim, M Saiful Bari, Thibault Fevry, Zaid Alyafeai, Manan Dey, Andrea Santilli, Zhiqing Sun, Srulik Ben-david, Canwen Xu, Gunjan Chhablani, Han Wang, Jason Fries, Maged Al-shaibani, Shanya Sharma, Urmish Thakker, Khalid Almubarak, Xiangru Tang, Dragomir Radev, Mike Tian-jian Jiang, Alexander Rush
| Challenge: | PromptSource is a system for creating, sharing, and using natural language prompts . prompts are used to train and query language models in zero-shot learning settings . |
| Approach: | PromptSource is a system for creating, sharing, and using natural language prompts . et al.: using prompts to train and query language models is emerging area in NLP . they propose a templating language for defining data-linked prompts, a user interface that iterates on prompt development . |
| Outcome: | PromptSource is a system for creating, sharing, and using natural language prompts . it has a templating language for defining data-linked prompts and a community-driven set of guidelines . |
Datasets: A Community Library for Natural Language Processing (2021.emnlp-demo)
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Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, Abhishek Thakur, Patrick von Platen, Suraj Patil, Julien Chaumond, Mariama Drame, Julien Plu, Lewis Tunstall, Joe Davison, Mario Šaško, Gunjan Chhablani, Bhavitvya Malik, Simon Brandeis, Teven Le Scao, Victor Sanh, Canwen Xu, Nicolas Patry, Angelina McMillan-Major, Philipp Schmid, Sylvain Gugger, Clément Delangue, Théo Matussière, Lysandre Debut, Stas Bekman, Pierric Cistac, Thibault Goehringer, Victor Mustar, François Lagunas, Alexander Rush, Thomas Wolf
| Challenge: | Contemporary NLP systems use many different datasets at significantly varying scale and level of annotation. |
| Approach: | a community library for contemporary NLP is available at https://github.com/datasets . the library includes more than 650 unique datasets and has more than 250 contributors a year after its initial development . |
| Outcome: | the library includes more than 650 unique datasets and has more than 250 contributors . it supports a variety of cross-dataset research projects and shared tasks . |
Detoxifying Language Models Risks Marginalizing Minority Voices (2021.naacl-main)
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| Challenge: | Existing detoxification techniques have been proposed to mitigate toxic LM generations . e.g., detoxification makes LMs more brittle to distribution shift, especially on language used by marginalized groups . |
| Approach: | They propose to use detoxification techniques to reduce toxic LM generations without affecting perplexity or generation quality on nontoxic inputs. |
| Outcome: | The proposed methods hurt equity on language used by marginalized groups, the authors show . they show that detoxification makes LMs more brittle to distribution shift, they say . |
Estimating Large Language Model Capabilities without Labeled Test Data (2023.findings-emnlp)
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| Challenge: | Large Language Models have shown impressive ability to perform in-context learning from only a few examples, but their accuracy varies widely from task to task. |
| Approach: | They propose a method that trains a meta-model using LLM confidence scores as features to perform ICL accuracy estimation. |
| Outcome: | The proposed method improves over baselines across 7 out of 12 settings and achieves the same accuracy as evaluating on 40 sampled examples per task. |
Automated Crossword Solving (2022.acl-long)
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| Challenge: | Using neural question answering models, our system generates answer candidates and then combines loopy belief propagation with local search to find full puzzle solutions. |
| Approach: | They propose a new approach to automatically solving crossword puzzles that uses neural question answering models and loopy belief propagation with local search to find full puzzle solutions. |
| Outcome: | The proposed system outperforms even the best human solvers and can solve crosswords from a wide range of domains with perfect accuracy. |
Contrastive Novelty-Augmented Learning: Anticipating Outliers with Large Language Models (2023.acl-long)
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| Challenge: | Existing methods for classification are overly confident on unseen examples . despite recent advances in NLP, some categories of distribution shift still pose serious challenges. |
| Approach: | They propose a method that generates OOD examples representative of novel classes and trains to decrease confidence on them. |
| Outcome: | The proposed method improves classifiers' ability to detect and abstain on novel class examples over previous methods by 2.3% and 5.5% over previous approaches. |