A team experimented with using a large language model, DeepSeek-V4.1-Flash, to orchestrate four smaller Qwen3.5-9B models for the task of reverse engineering software binaries. The setup involved DeepSeek disassembling code and assigning tasks, while the Qwen models performed the rewriting. An oracle model verified the correctness of the rewritten code. While the team approach was more costly and time-consuming for smaller tasks compared to DeepSeek operating alone, it led to interesting developments in prompt engineering, including the creation of a lookup tool for workers to access function signatures and memory layouts. AI
IMPACT Demonstrates potential for LLM orchestration of smaller models in complex tasks like reverse engineering.
RANK_REASON Experiment using LLMs to orchestrate smaller models for a specific task. [lever_c_demoted from research: ic=1 ai=1.0]
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