Author

Md. Faiyaz Abdullah Sayeedi

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Preprint Aug 2026

Time Present and Time Past: Benchmarking Large Language Models on Temporally Evolving Document Understanding

Evolving documents, such as laws, tax codes, and software documentation, are amended, replaced, and sometimes reverted over time, so a question has different correct answers at different dates. In contrast to encyclopedic knowledge, where an old fact is simply overwritten, an amendment is itself an official text that s...

M. Sobhani, Md. Faiyaz Abdullah Sayeedi, F. Chowdhury et al. · 1 citation · ⚡1

#machine learning Preprint Sep 2026

Teach Yourself Where to Look: On-Policy Attention Self-Distillation for Reasoning

On-Policy Attention Self-Distillation (OPASD), which complements token-level supervision with solution-conditioned attention distillation, shows that solution-conditioned attention provides a complementary supervision signal that makes on-policy self-distillation more accurate, stable, and compute-efficient.

Safaeid Hossain Arib, Rabeya Akter, I. N. Swapnil et al. · 0 citations

#natural language process... Preprint Sep 2026

To What Extent Do Large Language Models Understand Bangla Idioms?

Idiomatic expressions are an integral part of natural language, reflecting cultural nuances and posing unique challenges for computational models, particularly in low-resource languages. In this paper, we present the first large-scale benchmark dataset of Bangla idioms, complemented by a synthetic multiple-choice quest...

Mousumi Akter, Md. Faiyaz Abdullah Sayeedi, Nurul Labib Sayeedi et al. · 0 citations

#small language model Preprint Aug 2026

Do Large Language Models Play Six Degrees of Separation? Measuring Topological Compression in Long-Context Manifolds

This work mathematically formalizes how transformers execute abstract reasoning and provides a novel, strictly geometric signature for evaluating factual reliability, proving that deep LLM latent spaces natively organize into Small-World networks.

Md. Faiyaz Abdullah Sayeedi · 0 citations