Asia
Stopping Bayesian Optimization with Probabilistic Regret Bounds
Monte Carlo stopping rules in a manner that is both sample efficient and robust to estimation error.
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.
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
Supplementary Material: Einsum Benchmark Mark Blacher
For what purpose was the dataset created? The dataset was created with two primary purposes. First, it serves as a benchmark for einsum libraries, enabling the assessment of both the efficiency in determining contraction paths and the performance in executing einsum expressions. The dataset instances were created by the authors. Who funded the creation of the dataset?
