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TinyAudio is introduced, a compact flow-matching-based TTA model for low-resource deployment that achieves competitive generation quality on AudioCaps and TTA-Bench and demonstrates a practical quality-footprint trade-off for low-resource TTA deployment.
Omni Demand Understanding is established as a distinct multimodal contextual inference problem: given an interaction stream, a model must detect whether a user demand is present and infer intent from multimodal and conversational context, and ODU is evaluated along five dimensions, covering both single-turn and multi-t...
AuK, an open-source foundational model that unifies speech generation and editing through a common interface of natural-language instructions and audio context, is introduced and leading performance on zero-shot and instruction-controlled speech generation and general instruction-guided editing is demonstrated.
EmoDialogue, a bilingual dataset providing necessary fine-grained supervision through response pairs with rigorously defined EI gradations, and EmoS, a specialized evaluator model optimized via Supervised Fine-Tuning and Group Relative Policy Optimization, are introduced, establishing a foundational framework for advan...
This work presents \method, a training-free sparse-attention system that improves the distributed execution efficiency of adaptive sparse attention under multi-GPU sequence parallelism.
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