Papers by Nafew Azim
Adaptive Weighted Proxy Tuning: Efficient Gray-Box Steering for Image Captioning. (2026.acl-industry)
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| Challenge: | Proxy tuning is a decoding-time approach that fails to account for instance-specific variations in model certainty and domain shift. |
| Approach: | They propose a gray-box steering framework that dynamically modulates the logit contributions of a large base model, a fine-tuned expert, and an untune . |
| Outcome: | Adaptive Weighted Proxy Tuning achieves performance parity with fine-tuned models while remaining parameter-free. |
AutoDSPy: Automating Modular Prompt Design with Reinforcement Learning for Small and Large Language Models (2025.emnlp-industry)
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Nafew Azim, Abrar Ur Alam, Hasan Bin Omar, Abdullah Mohammad Muntasir Adnan Jami, Jawad Ibn Ahad, Muhammad Rafsan Kabir, Md. Ismail Hossain, Fuad Rahman, Mohammad Ruhul Amin, Shafin Rahman, Nabeel Mohammed
| Challenge: | Large Language Models excel at complex reasoning tasks, yet their performance hinges on the quality of their prompts and pipeline structures. |
| Approach: | They propose a framework that fully automates large language models' pipeline construction using reinforcement learning. |
| Outcome: | Experimental results show that autoDSPy outperforms DSPy benchmarks in accuracy gains and time. |