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About Mert Saglam
Mert Saglam is an individual researcher whose work focuses on LLM inference optimization and reinforcement learning. He is currently pursuing a PhD at the University of Washington, where he solved the Erdős-Simonovits conjecture, open since 1982, by studying random processes through the lens of relative entropy. His recent projects include dts, a sequence-to-sequence TypeScript to JavaScript compiler built on Qwen2.5 and trained with novel info-theoretic reinforcement learning algorithms. He has also published research on streaming targeted voice separation for on-device speech recognition, presented at Interspeech 2020.
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