Papers by Danial Namazifard

2 papers
Comparative Study of Multilingual Idioms and Similes in Large Language Models (2025.coling-main)

Copied to clipboard

Challenge: figurative language is one of the most challenging aspects of human language for LLMs to comprehend .
Approach: They evaluate LLMs using two multilingual datasets on simile and idiom interpretation and two new evaluation sets for Persian . they find prompt engineering methods are generally effective, but their success varies by figurative type, language, and model.
Outcome: The proposed models perform better in simile and idiom interpretations across languages and figurative types.
Benchmarking Large Language Models for Persian: A Preliminary Study Focusing on ChatGPT (2024.lrec-main)

Copied to clipboard

Challenge: a new study examines the efficacy of large language models (LLMs) for Persian . ChatGPT and LLMs have shown remarkable performance in English, but their efficiency for low-resource languages remains an open question.
Approach: They present a benchmarking study of large language models (LLMs) for Persian . they focus on GPT-3.5-turbo, but also GPT-4 and OpenChat-3.5 .
Outcome: The proposed model performs better in Persian than other low-resource languages . the study is the first comprehensive benchmarking of large language models .

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations