3 ms·
LLMs are by nature probabilistic, which is why they work reasonably well for "imprecise" domains like natural language processing. Expecting one to do decompila
by userbinator 3y ago
LLMs are by nature probabilistic, which is why they work reasonably well for "imprecise" domains like natural language processing. Expecting one to do decompilation, or disassembly for that matter, is IMHO very much a "wrong tool for the job" --- but perhaps it's just an exploratory exercise for the "just use an LLM" meme that seems to be a common trend these days.
The bigger argument against the effectiveness of this approach is that existing decompilers can already do a much better job with far less processing power.
- czl 3y agoIn the future efficient rule based compilers and decompiler may be generated by AI systems trained on inputs and outputs of what we use today. This effort is an exploration to find a radically different AI way that may give superior results. Yes. For all the reasons you give above, AI for this job is not practical today.
- kolinko 3y agoLLMs are also good at connecting the dots and figuring out patterns in a program. For this case it's ok if they miss even 99% of the times, because you can formally verify which solution is correct, and checking a 100 solutions is orders of magnitude faster than checking millions/billions/trillions of possibilities that a traditional solver needs to check.