activity
20192026
most citedPhylogeny-Inspired Adaptation of Multilingual Models to New Languages

6 citations · 17 across the 18 of their papers we have counts for

collaborators

19 papers

cs.CL2026

IDIOLEX: Unified and Continuous Representations for Idiolectal and Stylistic Variation

Anjali Kantharuban, Aarohi Srivastava, Fahim Faisal +5

Existing sentence representations primarily encode what a sentence says, rather than how it is expressed, even though the latter is important for many applications. In contrast, we…

cs.CL2025

Aligning Multilingual Reasoning with Verifiable Semantics from a High-Resource Expert Model

Fahim Faisal, Kaiqiang Song, Song Wang +4

While reinforcement learning has advanced the reasoning abilities of Large Language Models (LLMs), these gains are largely confined to English, creating a significant performance d…

cs.CL2024★ 1 cited

Dialectal Toxicity Detection: Evaluating LLM-as-a-Judge Consistency Across Language Varieties

Fahim Faisal, Md Mushfiqur Rahman, Antonios Anastasopoulos

There has been little systematic study on how dialectal differences affect toxicity detection by modern LLMs. Furthermore, although using LLMs as evaluators ("LLM-as-a-judge") is a…

cs.CL2024

Data-Augmentation-Based Dialectal Adaptation for LLMs

Fahim Faisal, Antonios Anastasopoulos

This report presents GMUNLP's participation to the Dialect-Copa shared task at VarDial 2024, which focuses on evaluating the commonsense reasoning capabilities of large language mo…

cs.CL2024

An Efficient Approach for Studying Cross-Lingual Transfer in Multilingual Language Models

Fahim Faisal, Antonios Anastasopoulos

The capacity and effectiveness of pre-trained multilingual models (MLMs) for zero-shot cross-lingual transfer is well established. However, phenomena of positive or negative transf…

cs.CL2024

DIALECTBENCH: A NLP Benchmark for Dialects, Varieties, and Closely-Related Languages

Fahim Faisal, Orevaoghene Ahia, Aarohi Srivastava +4

Language technologies should be judged on their usefulness in real-world use cases. An often overlooked aspect in natural language processing (NLP) research and evaluation is langu…

cs.CL2023★ 1 cited

To token or not to token: A Comparative Study of Text Representations for Cross-Lingual Transfer

Md Mushfiqur Rahman, Fardin Ahsan Sakib, Fahim Faisal +1

Choosing an appropriate tokenization scheme is often a bottleneck in low-resource cross-lingual transfer. To understand the downstream implications of text representation choices,…

cs.CL2023

Multilingual Text Representation

Fahim Faisal

Modern NLP breakthrough includes large multilingual models capable of performing tasks across more than 100 languages. State-of-the-art language models came a long way, starting fr…

cond-mat.supr-con2023★ 5 cited

Investigation on Machine Learning Based Approaches for Estimating the Critical Temperature of Superconductors

Fatin Abrar Shams, Rashed Hasan Ratul, Ahnaf Islam Naf +4

Superconductors have been among the most fascinating substances, as the fundamental concept of superconductivity as well as the correlation of critical temperature and superconduct…

cs.CL2023★ 2 cited

GlobalBench: A Benchmark for Global Progress in Natural Language Processing

Yueqi Song, Catherine Cui, Simran Khanuja +9

Despite the major advances in NLP, significant disparities in NLP system performance across languages still exist. Arguably, these are due to uneven resource allocation and sub-opt…

cs.CL2023

GMNLP at SemEval-2023 Task 12: Sentiment Analysis with Phylogeny-Based Adapters

Md Mahfuz Ibn Alam, Ruoyu Xie, Fahim Faisal +1

This report describes GMU's sentiment analysis system for the SemEval-2023 shared task AfriSenti-SemEval. We participated in all three sub-tasks: Monolingual, Multilingual, and Zer…

cs.CL2022★ 2 cited

Geographic and Geopolitical Biases of Language Models

Fahim Faisal, Antonios Anastasopoulos

Pretrained language models (PLMs) often fail to fairly represent target users from certain world regions because of the under-representation of those regions in training datasets.…

cs.CL2022★ 6 cited

Phylogeny-Inspired Adaptation of Multilingual Models to New Languages

Fahim Faisal, Antonios Anastasopoulos

Large pretrained multilingual models, trained on dozens of languages, have delivered promising results due to cross-lingual learning capabilities on variety of language tasks. Furt…

cs.CL2021

Dataset Geography: Mapping Language Data to Language Users

Fahim Faisal, Yinkai Wang, Antonios Anastasopoulos

As language technologies become more ubiquitous, there are increasing efforts towards expanding the language diversity and coverage of natural language processing (NLP) systems. Ar…

cs.CL2021

SD-QA: Spoken Dialectal Question Answering for the Real World

Fahim Faisal, Sharlina Keshava, Md Mahfuz ibn Alam +1

Question answering (QA) systems are now available through numerous commercial applications for a wide variety of domains, serving millions of users that interact with them via spee…

cs.CL2021

Investigating Post-pretraining Representation Alignment for Cross-Lingual Question Answering

Fahim Faisal, Antonios Anastasopoulos

Human knowledge is collectively encoded in the roughly 6500 languages spoken around the world, but it is not distributed equally across languages. Hence, for information-seeking qu…

cs.SE2021

Code to Comment Translation: A Comparative Study on Model Effectiveness & Errors

Junayed Mahmud, Fahim Faisal, Raihan Islam Arnob +2

Automated source code summarization is a popular software engineering research topic wherein machine translation models are employed to "translate" code snippets into relevant natu…

cs.SI2019

Mining Temporal Evolution of Knowledge Graph and Genealogical Features for Literature-based Discovery Prediction

Nazim Choudhury, Fahim Faisal, Matloob Khushi

Literature-based knowledge discovery process identifies the important but implicit relations among information embedded in published literature. Existing techniques from Informatio…

cs.IR2019

Disease Identification From Unstructured User Input

Fahim Faisal, Shafkat Ahmed Bhuiyan, Abu Raihan Mostofa Kamal

A method to identify probable diseases from the unstructured textual input (eg, health forum posts) by incorporating a lexicographic and semantic feature based two-phase text class…