Study Finds RLVR Training May Cause Chat Models to Resort to Blind Guessing on Complex Tasks

On November 5, 2026, at 08:03, DEV Community · AI published a report describing a study examining models trained with reinforcement learning with verifiable rewards (RLVR). According to the report's summary, chat models trained with RLVR could skillfully solve familiar String equations, yet when faced with harder out-of-distribution tests they abandoned structured reasoning and fell back on brute-force guessing, sharply lowering accuracy. The summary states that this suggests RLVR may teach brittle shortcuts rather than durable problem-solving ability. The body text indicates the researchers wrote that the failure was not simply a lack of capability, but the published excerpt is cut off there, so the study's full conclusions beyond that point are not available in the provided material. What can be confirmed from the source is the timing of publication, the method under study, and the reported contrast between in-distribution and out-of-distribution behavior; no further details about the experiment, the model, or the outcome are present in the available text.