54 citations · 108 across the 20 of their papers we have counts for
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Encoder-Decoder Diffusion Language Models for Efficient Training and Inference
Marianne Arriola, Yair Schiff, Hao Phung +2
Discrete diffusion models enable parallel token sampling for faster inference than autoregressive approaches. However, prior diffusion models use a decoder-only architecture, which…
d2: Improving Reasoning in Diffusion Language Models via Trajectory Likelihood Estimation
Guanghan Wang, Gilad Turok, Yair Schiff +2
While diffusion language models (DLMs) have achieved competitive performance in text generation, improving their reasoning ability with reinforcement learning remains an active res…
Remasking Discrete Diffusion Models with Inference-Time Scaling
Guanghan Wang, Yair Schiff, Subham Sekhar Sahoo +1
Part of the success of diffusion models stems from their ability to perform iterative refinement, i.e., repeatedly correcting outputs during generation. However, modern masked disc…