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This work establishes a robust dataset and evaluation benchmark for prosody-aware computational Sanskrit recitation by Benchmarking state-of-the-art TTS architectures via an automated UTMOS (neural MOS) predictor demonstrates that XTTS-v2 achieves the highest perceptual quality.
This work introduces CoDA, a framework in which a simulation data engine and an action policy co-evolve through a shared heterogeneous memory of environment construction, policy failures, and learning progress, and proposes Text2potential to convert these diagnoses into staged potentials for action-chunk value learning...
GraphVid is introduced, a graph-conditioned image-to-video generation model that enables interactive control through structured interaction graphs that delivers strong controllability and video quality and highlights the potential of structured semantic interfaces as a powerful paradigm for controllable video generatio...
Video editing spans diverse editing paradigms, yet achieving high-quality instruction-guided and subject-guided editing within a single unified framework remains challenging. We introduce EditVid, a training-free framework combining sparse causal memory for local coherence, correspondence-based post-attention token inj...
ViTAL-X, a lightweight model that equips frozen image-text backbones with temporal awareness while preserving their foundational spatial knowledge, achieves state-of-the-art performance and demonstrates that targeted, high-quality temporal alignment provides a highly efficient alternative to pure scaling.
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