Markus Boese — accepted AI-conference papers

2022

LINGUIST: Language Model Instruction Tuning to Generate Annotated Utterances for Intent Classification and Slot Tagging

Andy Rosenbaum, Saleh Soltan, Wael Hamza, Yannick Versley, Markus Boese

COLING 2022main

We present LINGUIST, a method for generating annotated data for Intent Classification and Slot Tagging (IC+ST), via fine-tuning AlexaTM 5B, a 5-billion-parameter multilingual sequence-to-sequence (seq2seq) model, on a flexible instruction prompt. In a 10-shot novel intent setting for the SNIPS datas…

Cited by 36 Source ↗PDF ↗code ↗Scholar ↗

2020

Leveraging User Paraphrasing Behavior In Dialog Systems To Automatically Collect Annotations For Long-Tail Utterances

Tobias Falke, Markus Boese, Daniil Sorokin, Caglar Tirkaz, Patrick Lehnen

COLING 2020industry

In large-scale commercial dialog systems, users express the same request in a wide variety of alternative ways with a long tail of less frequent alternatives. Handling the full range of this distribution is challenging, in particular when relying on manual annotations. However, the same users also p…

Cited by 21 Source ↗PDF ↗code ↗Scholar ↗