Text Based

Research on text-based methods focuses on improving the understanding, generation, and analysis of textual data, leveraging advancements in large language models (LLMs) and multimodal models. Current efforts concentrate on enhancing causal inference from textual data, mitigating issues like hallucinations and bias in LLM outputs, and developing methods for detecting AI-generated text. This work has significant implications for various fields, including digital forensics, content moderation, and the development of more robust and reliable AI systems.