Genre
AdaptiveISP: Learning an Adaptive Image Signal Processor for Object Detection Y ujin Wang
Image Signal Processors (ISPs) play a fundamental role in camera systems.
Learning segmentation from point trajectories
Segmentation, the task of delineating and isolating distinct objects, is a fundamental problem in computer vision. Much of the current approaches are supervised, relying on expensive manual annotations.
Context-Aware Testing: A New Paradigm for Model Testing with Large Language Models
The predominant de facto paradigm of testing ML models relies on either using only held-out data to compute aggregate evaluation metrics or by assessing the performance on different subgroups.
When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Models Yinghui Li
Inspired by the above motivation, we collect real cunning texts as our raw data from a famous Chinese online forum, the "Ruozhiba" (retard forum)
SRFUND: A Multi-Granularity Hierarchical Structure Reconstruction Benchmark in Form Understanding
Accurate identification and organizing of textual content is crucial for the automation of document processing in the field of form understanding. Existing datasets,
Functional Gradient Flows for Constrained Sampling
While successful, these methods are mainly designed for sampling from unconstrained domains.