Question Answering Benchmark

Question answering (QA) benchmarks are crucial for evaluating the capabilities of large language models (LLMs) across diverse domains and complexities. Current research focuses on developing benchmarks that assess LLMs' abilities to handle long-context inputs, reason across multiple documents and modalities (e.g., video and text), and accurately answer questions in low-resource languages and specialized fields like economics and healthcare. These benchmarks are vital for identifying strengths and weaknesses in LLMs, guiding model improvements, and ultimately advancing the development of more reliable and robust AI systems for various applications.