Language Input

Language input research focuses on how models process and understand diverse linguistic data, aiming to improve the robustness and accuracy of natural language processing (NLP) systems. Current efforts concentrate on handling multilingual inputs, noisy or unconventional text (including adversarial examples), and incorporating visual information, often leveraging large language models (LLMs) and multimodal architectures. This work is crucial for advancing the capabilities of AI systems across various applications, from machine translation and question answering to robotics and assistive technologies, by enabling them to better understand and respond to the complexities of human language in real-world scenarios.