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Even though my dataset is very small, I think it's sufficient to conclude that LLMs can't consistently reason. Also their reasoning performance gets worse as the SAT instance grows, which may be due to the context window becoming too large as the model reasoning progresses, and it gets harder to remember original clauses at the top of the context. A friend of mine made an observation that how complex SAT instances are similar to working with many rules in large codebases. As we add more rules, it gets more and more likely for LLMs to forget some of them, which can be insidious. Of course that doesn't mean LLMs are useless. They can be definitely useful without being able to reason, but due to lack of reasoning, we can't just write down the rules and expect that LLMs will always follow them. For critical requirements there needs to be some other process in place to ensure that these are met.
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This week, check out one of the most critically acclaimed international films of 2025, as Iranian director Jafar Panahi's It Was Just an Accident comes to digital. Winner of the Palme d'Or at this year's Cannes Film Festival, and nominated for four Golden Globes and two Oscars, it's a major awards season contender for good reason. This tale of former political prisoners trying to get revenge on the man they believe to be their former torturer is equal parts darkly funny and a scathing critique of authoritarianism.