3 citations · 9 across the 5 of their papers we have counts for
5 papers
Assessing Language Models' Worldview for Fiction Generation
Aisha Khatun, Daniel G. Brown
The use of Large Language Models (LLMs) has become ubiquitous, with abundant applications in computational creativity. One such application is fictional story generation. Fiction i…
TruthEval: A Dataset to Evaluate LLM Truthfulness and Reliability
Aisha Khatun, Daniel G. Brown
Large Language Model (LLM) evaluation is currently one of the most important areas of research, with existing benchmarks proving to be insufficient and not completely representativ…
Authorship Attribution in Bangla Literature (AABL) via Transfer Learning using ULMFiT
Aisha Khatun, Anisur Rahman, Md Saiful Islam +2
Authorship Attribution is the task of creating an appropriate characterization of text that captures the authors' writing style to identify the original author of a given piece of…
Reliability Check: An Analysis of GPT-3's Response to Sensitive Topics and Prompt Wording
Aisha Khatun, Daniel G. Brown
Large language models (LLMs) have become mainstream technology with their versatile use cases and impressive performance. Despite the countless out-of-the-box applications, LLMs ar…
Bits of Grass: Does GPT already know how to write like Whitman?
Piotr Sawicki, Marek Grzes, Fabricio Goes +3
This study examines the ability of GPT-3.5, GPT-3.5-turbo (ChatGPT) and GPT-4 models to generate poems in the style of specific authors using zero-shot and many-shot prompts (which…