Papers by Ethan Fetaya

1 papers
LR-DWM: Efficient Watermarking for Diffusion Language Models (2026.findings-acl)

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Challenge: Current methods for large language models rely on tokens being generated sequentially . left-right Diffusion watermarking uses a fixed, deterministic left-to-right order .
Approach: They propose a scheme that biases tokens based on both left and right neighbors . left-Right Diffusion Watermarking is a low-latency alternative to autoregressive models .
Outcome: The proposed method can be watermarked efficiently with minimal runtime and memory overhead.

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