ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot Filler

1 code implementation • 26 Mar 2024 • Paramita Mirza, Viju Sudhi, Soumya Ranjan Sahoo, Sinchana Ramakanth Bhat

State-of-the-art intent classification (IC) and slot filling (SF) methods often rely on data-intensive deep learning models, limiting their practicality for industry applications.

In-Context Learning intent-classification +4

CarExpert: Leveraging Large Language Models for In-Car Conversational Question Answering

no code implementations • 14 Oct 2023 • Md Rashad Al Hasan Rony, Christian Suess, Sinchana Ramakanth Bhat, Viju Sudhi, Julia Schneider, Maximilian Vogel, Roman Teucher, Ken E. Friedl, Soumya Sahoo

Large language models (LLMs) have demonstrated remarkable performance by following natural language instructions without fine-tuning them on domain-specific tasks and data.

Conversational Question Answering Retrieval

Natural Language Processing for Requirements Formalization: How to Derive New Approaches?

1 code implementation • 23 Sep 2023 • Viju Sudhi, Libin Kutty, Robin Gröpler

It shows that using current pre-trained NLP models requires less effort to create a set of rules and can be easily adapted to specific use cases and domains.