Task Language

Task language research focuses on developing and utilizing specialized languages to improve the efficiency and effectiveness of various tasks, particularly in artificial intelligence. Current research explores areas like simultaneous translation (using models like SeamlessM4T and AlignAtt), multi-lingual language understanding benchmarks (such as ArabicMMLU and IndoMMLU for evaluating model performance across diverse languages and cultures), and the creation of task-specific languages within reinforcement learning frameworks (e.g., using predicate representations to bridge natural language instructions and agent actions). These advancements are crucial for building more robust, adaptable, and human-centered AI systems capable of handling complex, multilingual tasks and improving cross-cultural communication.