EXPLORING CONTEXTUALIZED CONCEPTUALIZATION: AN EVALUATION OF PROMPT-DRIVEN RESPONSES IN DIVERSE LANGUAGE MODELS

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


MPhil Thesis Defence


Title: "EXPLORING CONTEXTUALIZED CONCEPTUALIZATION: AN EVALUATION OF
PROMPT-DRIVEN RESPONSES IN DIVERSE LANGUAGE MODELS"

By

Mr. Tsz Ho CHAN


Abstract:

Conceptualization, making abstraction and inference instantiation based on it,
is an essential part of intelligence, both human and artificial, for reasoning.
And it has long been regarded as a key component of Natural Language Processing
and Understanding for everyday situations.

With the fast-growing development of Pre-trained Language Models, more tasks
about conceptualization have been launched and tested, most of which are caring
conceptualization with context. However, the current experiments are focusing
on the traditional fine-tuning setting to let models fit into the provided
datasets but ignore the importance of the self-capable conceptualization
ability, which should be the true representative of the cognitive ability of
models. In this work, we propose some zero-shot experiments to explore the
influence of various prompts regarding models, the adaptability of prompts
regarding datasets, and try to find a challenging dataset to better examine
models. The results show that significant improvement can be produced with a
good choice of prompts.


Date:                   Thursday, 3 August 2023

Time:                   10:00am - 12:00noon

Venue:                  Room 3494
                        lifts 25/26

Committee Members:      Dr. Yangqiu Song (Supervisor)
                        Prof. Raymond Wong (Chairperson)
                        Dr. Minhao Cheng


**** ALL are Welcome ****