activity
20182025
most citedGraph-Based Multilingual Label Propagation for Low-Resource Part-of-Speech Tagging

1 citations · 2 across the 5 of their papers we have counts for

collaborators
Showing cs.CLShow all

6 papers · 1 filter

cs.CL2025

Through the LLM Looking Glass: A Socratic Probing of Donkeys, Elephants, and Markets

Molly Kennedy, Ayyoob Imani, Timo Spinde +2

Large Language Models (LLMs) are widely used for text generation, making it crucial to address potential bias. This study investigates ideological framing bias in LLM-generated art…

cs.CL20241 cited

MURI: High-Quality Instruction Tuning Datasets for Low-Resource Languages via Reverse Instructions

Abdullatif Köksal, Marion Thaler, Ayyoob Imani +3

Instruction tuning enhances large language models (LLMs) by aligning them with human preferences across diverse tasks. Traditional approaches to create instruction tuning datasets…

cs.CL2024

How Transliterations Improve Crosslingual Alignment

Yihong Liu, Mingyang Wang, Amir Hossein Kargaran +6

Recent studies have shown that post-aligning multilingual pretrained language models (mPLMs) using alignment objectives on both original and transliterated data can improve crossli…

cs.CL20221 cited

Graph-Based Multilingual Label Propagation for Low-Resource Part-of-Speech Tagging

Ayyoob Imani, Silvia Severini, Masoud Jalili Sabet +2

Part-of-Speech (POS) tagging is an important component of the NLP pipeline, but many low-resource languages lack labeled data for training. An established method for training a POS…

cs.CL2021

Graph Algorithms for Multiparallel Word Alignment

Ayyoob Imani, Masoud Jalili Sabet, Lütfi Kerem Şenel +3

With the advent of end-to-end deep learning approaches in machine translation, interest in word alignments initially decreased; however, they have again become a focus of research…

cs.CL2021

ParCourE: A Parallel Corpus Explorer for a Massively Multilingual Corpus

Ayyoob Imani, Masoud Jalili Sabet, Philipp Dufter +2

With more than 7000 languages worldwide, multilingual natural language processing (NLP) is essential both from an academic and commercial perspective. Researching typological prope…