Search Results for author: Roman Teucher

Found 2 papers, 0 papers with code

TextGraphs-16 Natural Language Premise Selection Task: Zero-Shot Premise Selection with Prompting Generative Language Models

no code implementations COLING (TextGraphs) 2022 Liubov Kovriguina, Roman Teucher, Robert Wardenga

Automated theorem proving can benefit a lot from methods employed in natural language processing, knowledge graphs and information retrieval: this non-trivial task combines formal languages understanding, reasoning, similarity search.

Automated Theorem Proving Information Retrieval +7

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

no code implementations14 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

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