Author

Jacqueline He

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#artificial intelligence Preprint Oct 2026

IsoVRBench: Video Reward Modeling Without Human Feedback

Video reward models are trained and evaluated on human preferences between videos that often differ simultaneously on properties such as prompt alignment, visual fidelity, motion, and generator identity. As a result, aggregate accuracy does not reveal which video properties a reward model can reliably distinguish. We c...

S. Li, Jacqueline He, Jia-Hui Chen et al. · 0 citations

#natural language process... Feb 2026

Anchored Decoding: Provably Reducing Copyright Risk for Any Language Model

Anchored Decoding is proposed, a plug-and-play inference-time method for suppressing verbatim copying that enables decoding from any risky LM trained on mixed-license data by keeping generation in bounded proximity to a permissively trained safe LM.

Jacqueline He, J. Hayase, Wen-tau Yih et al. · arXiv.org · 0 citations