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Runjia Li

Publications and source records attributed to Runjia Li.

22 records · Page 2Linked to original sources

OxfordTVG-HIC: Can Machine Make Humorous Captions from Images?

This paper presents OxfordTVG-HIC (Humorous Image Captions), a large-scale dataset for humour generation and understanding. Humour is an abstract, subjective, and context-dependent cognitive construct involving several cognitive factors, making it a challenging task to generate and interpret. Hence, humour generation and understanding can serve as a new task for evaluating the ability of deep-learning methods to process abstract and subjective information. Due to the scarcity of data, humour-related generation tasks such as captioning remain under-explored. To address this gap, OxfordTVG-HIC offers approximately 2.9M image-text pairs with humour scores to train a generalizable humour captioning model. Contrary to existing captioning datasets, OxfordTVG-HIC features a wide range of emotional and semantic diversity resulting in out-of-context examples that are particularly conducive to generating humour. Moreover, OxfordTVG-HIC is curated devoid of offensive content. We also show how OxfordTVG-HIC can be leveraged for evaluating the humour of a generated text. Through explainability analysis of the trained models, we identify the visual and linguistic cues influential for evoking humour prediction (and generation). We observe qualitatively that these cues are aligned with the benign violation theory of humour in cognitive psychology.

cs.CV↗

Real-time Blind Deblurring Based on Lightweight Deep-Wiener-Network

In this paper, we address the problem of blind deblurring with high efficiency. We propose a set of lightweight deep-wiener-network to finish the task with real-time speed. The Network contains a deep neural network for estimating parameters of wiener networks and a wiener network for deblurring. Experimental evaluations show that our approaches have an edge on State of the Art in terms of inference times and numbers of parameters. Two of our models can reach a speed of 100 images per second, which is qualified for real-time deblurring. Further research may focus on some real-world applications of deblurring with our models.

cs.CV↗

Flexible Seamless 2-in-1 Design with Sample Size Adaptation

2-in-1 design (Chen et al. 2018) is becoming popular in oncology drug development, with the flexibility of using different endpoints at different decision time. Based on the observed interim data, sponsors choose either to seamlessly advance a small phase 2 trial to a full-scale confirmatory phase 3 trial with a pre-determined maximum sample size, or to remain in a phase 2 trial. This approach may increase efficiency in drug development but is rigid and requires a pre-specified fixed sample size. In this paper, we propose a flexible 2-in-1 design with sample size adaptation, while retains the advantage of allowing intermediate endpoint for interim decision. The proposed design reflects the needs of recent FDA's Project FrontRunner initiative to encourage using an earlier surrogate endpoint to potentially support accelerated approval with conversion to standard approval with long term endpoint from the same randomized study. Additionally, we identify the interim decision cut-off to allow conventional test procedure at the final analysis. Extensive simulation studies showed the proposed design require much smaller sample size and shorter timeline than the simple 2-in-1 design, while achieving similar power. A case study in multiple myeloma is used to demonstrate the benefits of the proposed design.

stat.ME↗

Marangoni Convection-Driven Laser Fountains and Waves on Free Surfaces of Liquids

It is well accepted that an outward Marangoni convection from a low surface tension region will make the surface depressed. Here, we report that this established perception is only valid for thin liquid films. Using surface laser heating, we show that in deep liquids a laser beam actually pulls up the fluid above the free surface generating fountains with different shapes. Whereas with decreasing liquid depth a transition from fountain to indentation with fountain in-indentation is observed. Further, high-speed imaging reveals a transient surface process before steady elevation is formed, and this dynamic deformation is subsequently utilized to resonantly excite giant surface waves by a modulated laser beam. Computational fluid dynamics models reveal the underlying flow patterns and quantify the depth-dependent and time-resolved surface deformations. Our discoveries and techniques have upended the century-old perception and opened up a new regime of interdisciplinary research and applications of Marangoni-induced interface phenomena and optocapillary fluidic surfaces-the control of fluids with light.

physics.flu-dyn↗