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RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models
Machine unlearning is a promising solution for efficiently removing specific knowledge by post hoc modifying models.
MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures
Evaluating large language models (LLMs) is challenging.
Statistical Multicriteria Benchmarking via the GSD-Front
For (3), we relax our proposed test using techniques from robust statistics and imprecise probabilities.
Masked Space-Time Hash Encoding for Efficient Dynamic Scene Reconstruction
In this paper, we propose the M asked S pace-T ime H ash encoding (MSTH), a novel method for efficiently reconstructing dynamic 3D scenes from multi-view or monoc-ular videos.
Neuro-Vision to Language: Enhancing Brain Recording-based Visual Reconstruction and Language Interaction
This setup enables efficient, high-quality visual reconstructions across subjects from one experimental trial.
Learning Motion Refinement for Unsupervised Face Animation
Existing methods typically adopted a prior-based motion model ( e.g ., the local affine motion