7 papers · 1 filter
UrduMMLU: A Massive Multitask Benchmark for Urdu Language Understanding
Ahmer Tabassum, Sarfraz Ahmad, Hasan Iqbal +3
Meaningful multilingual evaluation must test models in the target language and educational context. Urdu, spoken by more than 230 million people, lacks a broad MMLU-style benchmark…
UrduFactCheck: An Agentic Fact-Checking Framework for Urdu with Evidence Boosting and Benchmarking
Sarfraz Ahmad, Hasan Iqbal, Momina Ahsan +6
The rapid adoption of Large Language Models (LLMs) has raised important concerns about the factual reliability of their outputs, particularly in low-resource languages such as Urdu…
OpenFactCheck: A Unified Framework for Factuality Evaluation of LLMs
Hasan Iqbal, Yuxia Wang, Minghan Wang +4
The increased use of large language models (LLMs) across a variety of real-world applications calls for automatic tools to check the factual accuracy of their outputs, as LLMs ofte…
OpenFactCheck: Building, Benchmarking Customized Fact-Checking Systems and Evaluating the Factuality of Claims and LLMs
Yuxia Wang, Minghan Wang, Hasan Iqbal +3
The increased use of large language models (LLMs) across a variety of real-world applications calls for mechanisms to verify the factual accuracy of their outputs. Difficulties lie…
FRaN-X: FRaming and Narratives-eXplorer
Artur Muratov, Hana Fatima Shaikh, Vanshikaa Jani +21
We present FRaN-X, a Framing and Narratives Explorer that automatically detects entity mentions and classifies their narrative roles directly from raw text. FRaN-X comprises a two-…
NeuralNexus at BEA 2025 Shared Task: Retrieval-Augmented Prompting for Mistake Identification in AI Tutors
Numaan Naeem, Sarfraz Ahmad, Momina Ahsan +1
This paper presents our system for Track 1: Mistake Identification in the BEA 2025 Shared Task on Pedagogical Ability Assessment of AI-powered Tutors. The task involves evaluating…