activity
20232026
most citedHandling Realistic Label Noise in BERT Text Classification

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

A Parallel Cross-Lingual Benchmark for Multimodal Idiomaticity Understanding

Dilara Torunoğlu-Selamet, Dogukan Arslan, Rodrigo Wilkens +75

Potentially idiomatic expressions (PIEs) construe meanings inherently tied to the everyday experience of a given language community. As such, they constitute an interesting challen…

cs.CL2025

Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Review

Maha Tufail Agro, Atharva Kulkarni, Karima Kadaoui +2

Motivated by a growing research interest into automatic speech recognition (ASR), and the growing body of work for languages in which code-switching (CS) often occurs, we present a…

cs.CL2025

Profiling News Media for Factuality and Bias Using LLMs and the Fact-Checking Methodology of Human Experts

Zain Muhammad Mujahid, Dilshod Azizov, Maha Tufail Agro +1

In an age characterized by the proliferation of mis- and disinformation online, it is critical to empower readers to understand the content they are reading. Important efforts in t…

cs.SD2024

PALM: Few-Shot Prompt Learning for Audio Language Models

Asif Hanif, Maha Tufail Agro, Mohammad Areeb Qazi +1

Audio-Language Models (ALMs) have recently achieved remarkable success in zero-shot audio recognition tasks, which match features of audio waveforms with class-specific text prompt…

cs.CL2023★ 1 cited

Handling Realistic Label Noise in BERT Text Classification

Maha Tufail Agro, Hanan Aldarmaki

Labels noise refers to errors in training labels caused by cheap data annotation methods, such as web scraping or crowd-sourcing, which can be detrimental to the performance of sup…