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This work introduces SEABED, an audio-first question answering dataset designed to benchmark language and audio reasoning models on SEA speech, and evaluates not only answer accuracy, but also whether models'stated reasoning is grounded in the audio evidence.
D DuplexWorld introduces six worlds where voice agents are especially useful: banking, insurance, travel, healthcare and logistics, and Pathfinding, and shows that even the best voice agents leave substantial room for improvement on all 3 axes.
RL-ADA (Reinforcement Learning with Adversarial Dialogue Agents), a co-evolutionary training framework that eliminates this bottleneck by replacing human labels with consequence-based reward signals derived directly from measurable interaction outcomes, is presented.
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