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Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models
Hendrik Strobelt, Albert Webson, Victor Sanh +4
State-of-the-art neural language models can now be used to solve ad-hoc language tasks through zero-shot prompting without the need for supervised training. This approach has gaine…
GenNI: Human-AI Collaboration for Data-Backed Text Generation
Hendrik Strobelt, Jambay Kinley, Robert Krueger +3
Table2Text systems generate textual output based on structured data utilizing machine learning. These systems are essential for fluent natural language interfaces in tools such as…
Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models
Hendrik Strobelt, Sebastian Gehrmann, Michael Behrisch +3
Neural Sequence-to-Sequence models have proven to be accurate and robust for many sequence prediction tasks, and have become the standard approach for automatic translation of text…
LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks
Hendrik Strobelt, Sebastian Gehrmann, Hanspeter Pfister +1
Recurrent neural networks, and in particular long short-term memory (LSTM) networks, are a remarkably effective tool for sequence modeling that learn a dense black-box hidden repre…