Deep language models for the insurance domain
keywords DEEP LEARNING, NATURAL LANGUAGE PROCESSING
Reference persons FABRIZIO LAMBERTI, LIA MORRA
Research Groups DAUIN - GR-09 - GRAphics and INtelligent Systems - GRAINS
Description The ultimate goal of this activity is to explore the potential use of large language models (LLMs) and chatbots, such as GPT-2 and GPT-3, in the insurance domain. Multiple thesis are available to investigate one or more of the following topics: a) how to fine-tune an existing LLM, starting from open source and commercial solutions, to customize it for a target language (Italian) and domain (insurance/legal); b) exploiting the LLM to analyze insurance claims. Example of target tasks are: predict whether they should be reimbursed under a given policy, or classify the type of damages described. Different alternatives will be considered, including prompt engineering and traditional classifiers ; c) exploit how to use structured Knowledge Graphs (KGs) in order to fine-tune and/or expand the capabilities of a LLM. Experience with deep learning and Pytorch is a prerequisite. Good analytical skills are required. Prior NLP knowledge is preferred, but not required.
Required skills deep learning, pytorch
Deadline 20/02/2024 PROPONI LA TUA CANDIDATURA