Benchmarks miss real user needs—ExpectBench shows LLMs fall short
Standard LLM benchmarks rate models on synthetic tasks, but a new study shows they often miss what users actually expect. The authors collect real interaction data, build ExpectBench—a benchmark of user‑driven expectations—and demonstrate that existing models fall short. Their lightweight LENS framework improves alignment by conditioning responses on extracted expectations.