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Found 12 papers, 3 papers with code
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results
This paper presents a review for the NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement.
NTIRE 2025 Challenge on Cross-Domain Few-Shot Object Detection: Methods and Results
Cross-Domain Few-Shot Object Detection (CD-FSOD) poses significant challenges to existing object detection and few-shot detection models when applied across domains.
Cross-Domain Few-Shot
Cross-Domain Few-Shot Object Detection
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Location is Key: Leveraging Large Language Model for Functional Bug Localization in Verilog
Bug localization in Verilog code is a crucial and time-consuming task during the verification of hardware design.
Evaluating Usability and Engagement of Large Language Models in Virtual Reality for Traditional Scottish Curling
The results show that LLM-based chatbots significantly improve interactivity and engagement, creating a more dynamic and immersive learning environment.
Embedding Large Language Models into Extended Reality: Opportunities and Challenges for Inclusion, Engagement, and Privacy
Advances in artificial intelligence and human-computer interaction will likely lead to extended reality (XR) becoming pervasive.
Eye-tracked Virtual Reality: A Comprehensive Survey on Methods and Privacy Challenges
Latest developments in computer hardware, sensor technologies, and artificial intelligence can make virtual reality (VR) and virtual spaces an important part of human everyday life.
Retrieving High-Dimensional Quantum Steering From a Noisy Environment with N Measurement Settings
One of the most often implied benefits of high-dimensional (HD) quantum systems is to lead to stronger forms of correlations, featuring increased robustness to noise.
Quantum Physics
The Time Function of Stock Price
A deductive approach is used to derive the auto-correlation function, displacement formula and power spectral density of the stock price movement, which reveals not only the characteristics and rules of the movement but also the predictability of the stock price.
Auto-Model: Utilizing Research Papers and HPO Techniques to Deal with the CASH problem
In many fields, a mass of algorithms with completely different hyperparameters have been developed to address the same type of problems.
Autoregressive-Model-Based Methods for Online Time Series Prediction with Missing Values: an Experimental Evaluation
In this paper, we focus on online methods for AR-model-based time series prediction with missing values.
Predicting Splicing from Primary Sequence with Deep Learning
The splicing of pre-mRNAs into mature transcripts is remarkable for its precision, but the mechanisms by which the cellular machinery achieves such specificity are incompletely understood.
Impacts of Dirty Data: and Experimental Evaluation
Data quality issues have attracted widespread attention due to the negative impacts of dirty data on data mining and machine learning results.
