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This work investigates whether hybrid backbones can become effective DLMs by adapting Qwen3.5 at 0.8B, 2B, 4B, and 9B scales, and finds that they can be efficient starting points for adaptation.
TTCD achieves superior conditional generation performance and faster token processing by leveraging continuous space modeling and per-token timing, challenging the limitations of traditional discrete models.
