Language & Reasoning Lab

Models that understand the languages of two hundred and forty million people.

  • Urdu and regional-language benchmarks
  • Evaluation of reasoning
  • Retrieval and grounding
  • Efficient fine-tuning

Lab lead

Dr. Bilal Ahmed

Associate Professor · Head of the Language & Reasoning Lab

The lab studies how large language models represent, reason about and generate text — with a deliberate focus on Urdu, Punjabi, Sindhi and Pashto, which remain poorly served by systems trained on English-heavy corpora.

Current work includes a public benchmark suite for Urdu question answering, methods for measuring reasoning quality without leaking test data into training, and retrieval techniques that hold up on legal and administrative documents.

The lab collaborates with the Safety, Alignment & Governance Lab on evaluation infrastructure and with two provincial education departments on assistive tools for teachers.

Publications

  1. 2026
  2. 2026
    Paper

    UrduQA: A Contamination-Resistant Benchmark for Question Answering in Urdu

    Bilal Ahmed, Rafia Hussain, Ali Hassan, Sana Malik · ACL 2026 (Findings)