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cs.CL2026
LLM Output Detectability and Task Performance Can be Jointly Optimized
Koshiro Saito, Ryuto Koike, Masahiro Kaneko +1
Detecting machine-generated text is essential for transparency and accountability when deploying LLMs. Watermarking enables statistically reliable detection by biasing token distri…
cs.CL2026
Synthesizing Instruction-Tuning Datasets with Contrastive Decoding
Tatsuya Ichinose, Youmi Ma, Masanari Oi +2
Using responses generated by high-performing large language models (LLMs) for instruction tuning has become a widely adopted approach. However, the existing literature overlooks a…