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P2Flow is introduced, a phoneme-aware progressive flow matching (FM) framework designed for extreme SSR with three main strategies, which leverages phonetic information to reconstruct missing spectral components and employs a progressive architectural design that hierarchically restores distinct frequency regions.
Current LALMs can identify basic audio content but often fail to diagnose and reason about degradation, revealing a significant blind spot in their capabilities.
Stop wasting compute: this RL-trained orchestration policy adaptively decides when your embodied agent should reason with an LLM, slashing latency and boosting task success compared to fixed strategies.
