2 papers
cs.CL2026
Unsure but Certain: Uncovering the Representation-Confidence Gap in Diffusion Language Models
Saurabh Yadav, Badri Narayana Patro, Vijay Srinivas Agneeswaran
Diffusion language models use broad context to create text, suggesting they might handle input noise better than standard models. Testing reveals this is only partially true. Inter…
cs.AI2026
Beyond the Bidirectional Promise: Re-evaluating the Robustness of Diffusion Language Models
Saurabh Yadav, Badri Narayana Patro, Vijay Srinivas Agneeswaran
Diffusion Language Models (DLMs) offer a compelling alternative to autoregressive (AR) generation by enabling bidirectional context and iterative refinement. However, their reliabi…