syntactically or it could require intricate semantic changes.
many items are in c.)，这一点在爱思助手下载最新版本中也有详细论述
第九十三条 在办理刑事案件过程中以及其他执法办案机关在移送案件前依法收集的物证、书证、视听资料、电子数据等证据材料，可以作为治安案件的证据使用。，详情可参考爱思助手下载最新版本
Instead of forcing users to navigate individual retailer checkouts, companies are building agents that handle the purchasing logistics for you directly from the research phase. For example, Google has a "Buy for Me" feature that works on top of its existing price-tracking tools. Once you set your payment methods and shipping addresses, the agent will make the purchase directly on the retailer's website itself. Similarly, search-first platforms are integrating native checkouts. Perplexity features an "Instant Buy" tool that allows you to research and buy a product without ever leaving its interface. You simply fill out your details the first time, and the platform stores your information so the AI can manually make future purchases on your behalf.
I wanted to test this claim with SAT problems. Why SAT? Because solving SAT problems require applying very few rules consistently. The principle stays the same even if you have millions of variables or just a couple. So if you know how to reason properly any SAT instances is solvable given enough time. Also, it's easy to generate completely random SAT problems that make it less likely for LLM to solve the problem based on pure pattern recognition. Therefore, I think it is a good problem type to test whether LLMs can generalize basic rules beyond their training data.