3 citations · 3 across the 4 of their papers we have counts for
4 papers
Discrete Diffusion Language Models Are Training-Free Multi-Label Classifiers
Pawan Kumar
We present dLLM-SetScore, a training-free method that uses discrete masked-diffusion language models for multi-label text classification. For each candidate label, it asks a short…
Speculative Refinement: A Hybrid Autoregressive Diffusion Decoding Strategy and Its Behavior Across Benchmarks
Aditi Gupta, Neel Mishra, Kushagra Trivedi +1
How should we evaluate generation systems that combine autoregressive (AR) and diffusion decoding? We study this question through Speculative Refinement (SpecRef), a training-free…
Alignment and Safety of Diffusion Models via Reinforcement Learning and Reward Modeling: A Survey
Preeti Lamba, Kiran Ravish, Ankita Kushwaha +1
Diffusion models have become a central paradigm for image and multimodal generation, yet their deployment raises persistent questions about alignment, safety, preference satisfacti…
A Survey of Safe Reinforcement Learning and Constrained MDPs: A Technical Survey on Single-Agent and Multi-Agent Safety
Ankita Kushwaha, Kiran Ravish, Preeti Lamba +1
Safe Reinforcement Learning (SafeRL) is the subfield of reinforcement learning that explicitly deals with safety constraints during the learning and deployment of agents. This surv…