3 papers
cs.LG2026
Fork-dLLM: Avoiding the Flexibility Trap in Diffusion Language Models
Stipe Frković, Metod Jazbec, Christian A. Naesseth
Masked diffusion language models (dLLMs) have shown strong potential for faster inference through parallel token generation when combined with confidence-based samplers. However, r…
cs.LG2026
Re-evaluating Confidence Remasking in Masked Diffusion Language Models
Stipe Frkovic, Metod Jazbec, Dan Zhang +3
Masked diffusion language models (dLLMs) have recently emerged as a competitive alternative to autoregressive language models, with the promise of faster inference via parallel tok…
cs.CV2025
[Re] Improving Interpretation Faithfulness for Vision Transformers
Izabela Kurek, Wojciech Trejter, Stipe Frkovic +1
This work aims to reproduce the results of Faithful Vision Transformers (FViTs) proposed by arXiv:2311.17983 alongside interpretability methods for Vision Transformers from arXiv:2…