3 papers
cs.CV2026
On the Robustness of Watermarking for Autoregressive Image Generation
Andreas Müller, Denis Lukovnikov, Shingo Kodama +5
The proliferation of autoregressive (AR) image generators demands reliable detection and attribution of their outputs to mitigate misinformation, and to filter synthetic images fro…
cs.LG2026
Understanding Empirical Unlearning with Combinatorial Interpretability
Shingo Kodama, Niv Cohen, Micah Adler +1
While many recent methods aim to unlearn or remove knowledge from pretrained models, seemingly erased knowledge often persists and can be recovered in various ways. Because large f…
cs.CR2025
SimKey: A Semantically Aware Key Module for Watermarking Language Models
Shingo Kodama, Haya Diwan, Lucas Rosenblatt +2
The rapid spread of text generated by large language models (LLMs) makes it increasingly difficult to distinguish authentic human writing from machine output. Watermarking offers a…