Question and Answer Format

Question answering (QA) research focuses on developing systems capable of accurately and reliably responding to diverse question formats, from simple yes/no queries to complex, open-ended prompts. Current research emphasizes improving the factual accuracy of large language models (LLMs) by incorporating verification mechanisms and exploring their application in diverse fields, such as education and cybersecurity. These advancements leverage transformer-based architectures and techniques like chain-of-verification to mitigate issues like hallucination, while also addressing the challenges of adapting QA systems to low-resource languages. The resulting improvements have significant implications for various applications, including automated feedback systems, educational tools, and even cybersecurity threat analysis.