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Found 9 papers, 3 papers with code
Machine Learning Training on a Real Processing-in-Memory System
Our goal is to understand the potential of modern general-purpose PIM architectures to accelerate machine learning training.
An Experimental Evaluation of Machine Learning Training on a Real Processing-in-Memory System
Our K-Means clustering on PIM is $2. 8\times$ and $3. 2\times$ than state-of-the-art CPU and GPU versions, respectively.
TransPimLib: A Library for Efficient Transcendental Functions on Processing-in-Memory Systems
In order to provide support for transcendental (and other hard-to-calculate) functions in general-purpose PIM systems, we present \emph{TransPimLib}, a library that provides CORDIC-based and LUT-based methods for trigonometric functions, hyperbolic functions, exponentiation, logarithm, square root, etc.
Data-centric Graph Learning: A Survey
Recently, instead of designing more complex neural architectures as model-centric approaches, the attention of AI community has shifted to data-centric ones, which focuses on better processing data to strengthen the ability of neural models.
ToxicChat: Unveiling Hidden Challenges of Toxicity Detection in Real-World User-AI Conversation
This benchmark contains the rich, nuanced phenomena that can be tricky for current toxicity detection models to identify, revealing a significant domain difference compared to social media content.
Understanding the Multi-modal Prompts of the Pre-trained Vision-Language Model
In this paper, we conduct a direct analysis of the multi-modal prompts by asking the following questions: $(i)$ How do the learned multi-modal prompts improve the recognition performance?
Dual Mean-Teacher: An Unbiased Semi-Supervised Framework for Audio-Visual Source Localization
Audio-Visual Source Localization (AVSL) aims to locate sounding objects within video frames given the paired audio clips.
Cross Pseudo-Labeling for Semi-Supervised Audio-Visual Source Localization
Audio-Visual Source Localization (AVSL) is the task of identifying specific sounding objects in the scene given audio cues.
CoReS: Orchestrating the Dance of Reasoning and Segmentation
We believe that the act of reasoning segmentation should mirror the cognitive stages of human visual search, where each step is a progressive refinement of thought toward the final object.
