5 papers · 1 filter
PIG: Parallel Inconsistency Guidance for Accelerating Diffusion Language Models
Quentin Fruytier, Anton Xue, Sanjay Shakkottai +1
Diffusion language models accelerate generation by decoding multiple masked positions per forward pass. However, accuracy is known to drop when parallel decoding trajectories devia…
LESSER: Post-Training Data Selection with Output-Layer Gradients
Lyuxin David Zhang, Eric Wong, Surbhi Goel +1
The choice of post-training data for large language models substantially affects downstream performance. Gradient-based data selection is a popular approach that ranks training dat…
dQwen3.5: Hybrid-Attention Diffusion Language Models
Anton Xue, Litu Rout, Aditya Akella +3
Adapting a pretrained autoregressive (AR) model is a cost-efficient route to a diffusion language model (DLM). While nearly all such adaptations start from a full-attention transfo…
Missingness Bias Calibration in Feature Attribution Explanations
Shailesh Sridhar, Anton Xue, Eric Wong
Popular explanation methods often produce unreliable feature importance scores due to missingness bias, a systematic distortion that arises when models are probed with ablated, out…
AnCoder: Anchored Code Generation via Discrete Diffusion Models
Anton Xue, Litu Rout, Constantine Caramanis +1
Diffusion language models offer a compelling alternative to autoregressive code generation, enabling global planning and iterative refinement of complex program logic. However, exi…