activity
20202026
most citedGlot500: Scaling Multilingual Corpora and Language Models to 500 Languages

17 citations · 48 across the 21 of their papers we have counts for

collaborators

21 papers

cs.CL2026

Last Translation Benchmark

Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263

For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…

cs.CL2026★ 1 cited

Who Flips? Self- and Cross-Model Counterarguments Reveal Answer Instability in LLMs

Nafiseh Nikeghbal, Amir Hossein Kargaran, Shaghayegh Kolli +1

Standard accuracy benchmarks evaluate whether large language models (LLMs) reach correct answers. However, they do not test whether models maintain that answer when challenged by a…

cs.CL2026

GlotOCR Bench: OCR Models Still Struggle Beyond a Handful of Unicode Scripts

Amir Hossein Kargaran, Nafiseh Nikeghbal, Jana Diesner +2

Optical character recognition (OCR) has advanced rapidly with the rise of vision-language models, yet evaluation has remained concentrated on a small cluster of high- and mid-resou…

cs.CY2025

Insights from the ICLR Peer Review and Rebuttal Process

Amir Hossein Kargaran, Nafiseh Nikeghbal, Jing Yang +1

Peer review is a cornerstone of scientific publishing, including at premier machine learning conferences such as ICLR. As submission volumes increase, understanding the nature and…

cs.CL2025

CoBia: Constructed Conversations Can Trigger Otherwise Concealed Societal Biases in LLMs

Nafiseh Nikeghbal, Amir Hossein Kargaran, Jana Diesner

Improvements in model construction, including fortified safety guardrails, allow Large language models (LLMs) to increasingly pass standard safety checks. However, LLMs sometimes s…

cs.CL2025

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Guilherme Penedo, Hynek Kydlíček, Vinko Sabolčec +7

Pre-training state-of-the-art large language models (LLMs) requires vast amounts of clean and diverse text data. While the open development of large high-quality English pre-traini…

cs.CL2025

How Programming Concepts and Neurons Are Shared in Code Language Models

Amir Hossein Kargaran, Yihong Liu, François Yvon +1

Several studies have explored the mechanisms of large language models (LLMs) in coding tasks, but most have focused on programming languages (PLs) in a monolingual setting. In this…

cs.CL2025

Tracing Multilingual Factual Knowledge Acquisition in Pretraining

Yihong Liu, Mingyang Wang, Amir Hossein Kargaran +5

Large Language Models (LLMs) are capable of recalling multilingual factual knowledge present in their pretraining data. However, most studies evaluate only the final model, leaving…

cs.CL2025

On Relation-Specific Neurons in Large Language Models

Yihong Liu, Runsheng Chen, Lea Hirlimann +6

In large language models (LLMs), certain \emph{neurons} can store distinct pieces of knowledge learned during pretraining. While factual knowledge typically appears as a combinatio…

cs.CL2024

GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages

Amir Hossein Kargaran, François Yvon, Hinrich Schütze

The need for large text corpora has increased with the advent of pretrained language models and, in particular, the discovery of scaling laws for these models. Most available corpo…

cs.CL2024★ 1 cited

MEXA: Multilingual Evaluation of English-Centric LLMs via Cross-Lingual Alignment

Amir Hossein Kargaran, Ali Modarressi, Nafiseh Nikeghbal +3

English-centric large language models (LLMs) often show strong multilingual capabilities. However, their multilingual performance remains unclear and is under-evaluated for many ot…

cs.CL2024★ 1 cited

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.CL2024

MaskLID: Code-Switching Language Identification through Iterative Masking

Amir Hossein Kargaran, François Yvon, Hinrich Schütze

We present MaskLID, a simple, yet effective, code-switching (CS) language identification (LID) method. MaskLID does not require any training and is designed to complement current h…

cs.SE2024★ 1 cited

GIRT-Model: Automated Generation of Issue Report Templates

Nafiseh Nikeghbal, Amir Hossein Kargaran, Abbas Heydarnoori

Platforms such as GitHub and GitLab introduce Issue Report Templates (IRTs) to enable more effective issue management and better alignment with developer expectations. However, the…

cs.CL2023★ 16 cited

GlotLID: Language Identification for Low-Resource Languages

Amir Hossein Kargaran, Ayyoob Imani, François Yvon +1

Several recent papers have published good solutions for language identification (LID) for about 300 high-resource and medium-resource languages. However, there is no LID available…

cs.CL2023

GlotScript: A Resource and Tool for Low Resource Writing System Identification

Amir Hossein Kargaran, François Yvon, Hinrich Schütze

We present GlotScript, an open resource and tool for low resource writing system identification. GlotScript-R is a resource that provides the attested writing systems for more than…

cs.CL2023★ 17 cited

Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages

Ayyoob Imani, Peiqin Lin, Amir Hossein Kargaran +8

The NLP community has mainly focused on scaling Large Language Models (LLMs) vertically, i.e., making them better for about 100 languages. We instead scale LLMs horizontally: we cr…

cs.SE2023

GIRT-Data: Sampling GitHub Issue Report Templates

Nafiseh Nikeghbal, Amir Hossein Kargaran, Abbas Heydarnoori +1

GitHub's issue reports provide developers with valuable information that is essential to the evolution of a software development project. Contributors can use these reports to perf…

cs.CL2023★ 1 cited

MenuCraft: Interactive Menu System Design with Large Language Models

Amir Hossein Kargaran, Nafiseh Nikeghbal, Abbas Heydarnoori +1

Menu system design for user interfaces is a challenging task involving many design options and various human factors. For example, one crucial factor that designers need to conside…

cs.CR2020★ 6 cited

Wide-AdGraph: Detecting Ad Trackers with a Wide Dependency Chain Graph

Amir Hossein Kargaran, Mohammad Sadegh Akhondzadeh, Mohammad Reza Heidarpour +3

Websites use third-party ads and tracking services to deliver targeted ads and collect information about users that visit them. These services put users' privacy at risk, and that…

eess.SY2020★ 4 cited

Analytical Derivation and Comparison of Alarm Similarity Measures

Amir Hossein Kargaran, Amir Neshastegaran, Iman Izadi +1

An industrial process includes many devices, variables, and sub-processes that are physically or electronically interconnected. These interconnections imply some level of correlati…