Sebastian Gehrmann
9 papers in the PaperMetrix corpus
Papers by this author
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Margin Call: an Accessible Web-based Text Viewer with Generated Paragraph Summaries in the Margin
2019
We present Margin Call, an accessible webbased text viewer that automatically generates short summaries for each paragraph of the text and displays the summaries in the margin of the text next to the corresponding paragraph. …
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The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models
2020 · arXiv (Cornell University)
We present the Language Interpretability Tool (LIT), an open-source platform for visualization and understanding of NLP models. We focus on core questions about model behavior: Why did my model make this prediction? When does it …
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Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models
2021
Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann, Stuart Shieber, Tal Linzen, Yonatan Belinkov. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume …
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NL-Augmenter 🦎 → 🐍 A Framework for Task-Sensitive Natural Language Augmentation
2023 · Northern European Journal of Language Technology
Data augmentation is an important method for evaluating the robustness of and enhancing the diversity of training data for natural language processing (NLP) models. In this paper, we present NL-Augmenter, a new participatory Python-based natural …
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Bottom-Up Abstractive Summarization
2018
Neural network-based methods for abstractive summarization produce outputs that are more fluent than other techniques, but which can be poor at content selection. This work proposes a simple technique for addressing this issue: use a …
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exBERT: A Visual Analysis Tool to Explore Learned Representations in Transformer Models
2020
Large Transformer-based language models can route and reshape complex information via their multi-headed attention mechanism. Although the attention never receives explicit supervision, it can exhibit recognizable patterns following linguistic or positional information. Analyzing the learned …
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The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
2021
Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, Pawan Sasanka Ammanamanchi, Anuoluwapo Aremu, Antoine Bosselut, Khyathi Raghavi Chandu, Miruna-Adriana Clinciu, Dipanjan Das, Kaustubh Dhole, Wanyu Du, Esin Durmus, Ondřej Dušek, Chris Chinenye Emezue, Varun Gangal, Cristina Garbacea, …
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PaLM: Scaling Language Modeling with Pathways
2022 · arXiv (Cornell University)
Large language models have been shown to achieve remarkable performance across a variety of natural language tasks using few-shot learning, which drastically reduces the number of task-specific training examples needed to adapt the model to …
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BloombergGPT: A Large Language Model for Finance
2023 · arXiv (Cornell University)
The use of NLP in the realm of financial technology is broad and complex, with applications ranging from sentiment analysis and named entity recognition to question answering. Large Language Models (LLMs) have been shown to …