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cs.LG2026
Continuous-Utility Direct Preference Optimization
Muhammad Ahmed Mohsin, Muhammad Umer, Ahsan Bilal +6
Large language model reasoning is often treated as a monolithic capability, relying on binary preference supervision that fails to capture partial progress or fine-grained reasonin…
cs.LG2026
On the Fundamental Limits of LLMs at Scale
Muhammad Ahmed Mohsin, Muhammad Umer, Ahsan Bilal +13
Large Language Models (LLMs) have benefited enormously from scaling, yet these gains are bounded by five fundamental limitations: (1) hallucination, (2) context compression, (3) re…
cs.LG2025
Meta-Reinforcement Learning for Fast and Data-Efficient Spectrum Allocation in Dynamic Wireless Networks
Oluwaseyi Giwa, Tobi Awodunmila, Muhammad Ahmed Mohsin +2
The dynamic allocation of spectrum in 5G / 6G networks is critical to efficient resource utilization. However, applying traditional deep reinforcement learning (DRL) is often infea…