3 papers
cs.CL2026
SyRA-CS: Synthetic-to-Real Adaptation for Code-Switched ASR with Meta-Learning
Fadel Thior, Ahmer Tabassum, Haania Siddiqui +2
Code-switched (CS) automatic speech recognition (ASR) remains difficult because real CS speech is scarce and synthetic speech does not fully match it. We investigate whether synthe…
cs.CL2026
The Bottleneck Is Retrieval, Not Reading: Diagnosing Evidence-Based Generation with RAG for Long Context Question Answering
Debopriyo Banerjee, Owais Aijaz, Ahmer Tabassum +3
Retrieval-augmented generation (RAG) is the dominant paradigm for grounding large language models in external corpora, but its similarity-driven, chunked pipeline has structural bl…
cs.CL2026
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…