Top Two Answer

Research on "Top Two Answer" focuses on improving the accuracy and reliability of large language models (LLMs) in question-answering tasks, particularly addressing issues like hallucinations and biases. Current efforts concentrate on developing methods to enhance answer grounding, using techniques like retrieval-augmented generation (RAG) and incorporating visual or other contextual information to verify responses. This work is crucial for building trustworthy AI systems, with implications for various applications ranging from financial advice to medical diagnosis, where accurate and reliable information is paramount.