Search Results for author:
Found 7 papers, 4 papers with code
EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty
In this paper, we reconsider speculative sampling and derive two key observations.
RAIN: Your Language Models Can Align Themselves without Finetuning
We discover that by integrating self-evaluation and rewind mechanisms, unaligned LLMs can directly produce responses consistent with human preferences via self-boosting.
CARMA: Context-Aware Runtime Reconfiguration for Energy-Efficient Sensor Fusion
Autonomous systems (AS) are systems that can adapt and change their behavior in response to unanticipated events and include systems such as aerial drones, autonomous vehicles, and ground/aquatic robots.
Fusing Structural and Functional Connectivities using Disentangled VAE for Detecting MCI
In this paper, a novel hierarchical structural-functional connectivity fusing (HSCF) model is proposed to construct brain structural-functional connectivity matrices and predict abnormal brain connections based on functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI).
Direct-Effect Risk Minimization for Domain Generalization
In this work, we introduce the concepts of direct and indirect effects from causal inference to the domain generalization problem.
An optical biomimetic eyes with interested object imaging
We presented an optical system to perform imaging interested objects in complex scenes, like the creature easy see the interested prey in the hunt for complex environments.
AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?
With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved comparable results with inter-rater variability on many benchmark datasets.
