Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models

Kavli Affiliate: Wei Gao | First 5 Authors: Hongzhan Lin, Ziyang Luo, Wei Gao, Jing Ma, Bo Wang | Summary: The age of social media is flooded with Internet memes, necessitating a clear grasp and effective identification of harmful ones. This task presents a significant challenge due to the implicit meaning embedded in memes, which […]


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Research on the knee region of cosmic ray by using a novel type of electron-neutron detector array

Kavli Affiliate: Wei Gao | First 5 Authors: Bing-Bing Li, Xin-Hua Ma, Shu-Wang Cui, Hao-Kun Chen, Tian-Lu Chen | Summary: By accurately measuring composition and energy spectrum of cosmic ray, the origin problem of so called "keen" region (energy > 1 PeV) can be solved. However, up to the present, the results of the spectrum […]


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Predicting Viral Rumors and Vulnerable Users for Infodemic Surveillance

Kavli Affiliate: Wei Gao | First 5 Authors: Xuan Zhang, Wei Gao, , , | Summary: In the age of the infodemic, it is crucial to have tools for effectively monitoring the spread of rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be more susceptible to spreading such […]


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Uncertainty-aware No-Reference Point Cloud Quality Assessment

Kavli Affiliate: Wei Gao | First 5 Authors: Songlin Fan, Zixuan Guo, Wei Gao, Ge Li, | Summary: The evolution of compression and enhancement algorithms necessitates an accurate quality assessment for point clouds. Previous works consistently regard point cloud quality assessment (PCQA) as a MOS regression problem and devise a deterministic mapping, ignoring the stochasticity […]


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JustiLM: Few-shot Justification Generation for Explainable Fact-Checking of Real-world Claims

Kavli Affiliate: Wei Gao | First 5 Authors: Fengzhu Zeng, Wei Gao, , , | Summary: Justification is an explanation that supports the veracity assigned to a claim in fact-checking. However, the task of justification generation is previously oversimplified as summarization of fact-check article authored by fact-checkers. Therefore, we propose a realistic approach to generate […]


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AstroInformatics: Recommendations for Global Cooperation

Kavli Affiliate: Rana Adhikari | First 5 Authors: Ashish Mahabal, Pranav Sharma, Rana Adhikari, Mark Allen, Stefano Andreon | Summary: Policy Brief on "AstroInformatics, Recommendations for Global Collaboration", distilled from panel discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. The deliberations encompassed a wide array of topics, including […]


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Optical-parametric-amplification-enhanced background-free spectroscopy

Kavli Affiliate: Alireza Marandi | First 5 Authors: Mingchen Liu, Robert M. Gray, Arkadev Roy, Luis Ledezma, Alireza Marandi | Summary: Traditional absorption spectroscopy has fundamental difficulty in resolving small absorbance from strong background due to the instability of laser sources. Existing background-free methods in broadband vibrational spectroscopy help to alleviate this problem but face […]


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Experimental Upper Bounds for Resonance-Enhanced Entangled Two-Photon Absorption Cross Section of Indocyanine Green

Kavli Affiliate: Scott K. Cushing | First 5 Authors: Manni He, Bryce P. Hickam, Nathan Harper, Scott K. Cushing, | Summary: Resonant intermediate states have been proposed to increase the efficiency of entangled two-photon absorption (ETPA). Although resonance-enhanced ETPA (r-ETPA) has been demonstrated in atomic systems using bright squeezed vacuum, it has not been studied […]


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Real-time Neural Network Inference on Extremely Weak Devices: Agile Offloading with Explainable AI

Kavli Affiliate: Wei Gao | First 5 Authors: Kai Huang, Wei Gao, , , | Summary: With the wide adoption of AI applications, there is a pressing need of enabling real-time neural network (NN) inference on small embedded devices, but deploying NNs and achieving high performance of NN inference on these small devices is challenging […]


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ElasticTrainer: Speeding Up On-Device Training with Runtime Elastic Tensor Selection

Kavli Affiliate: Wei Gao | First 5 Authors: Kai Huang, Boyuan Yang, Wei Gao, , | Summary: On-device training is essential for neural networks (NNs) to continuously adapt to new online data, but can be time-consuming due to the device’s limited computing power. To speed up on-device training, existing schemes select trainable NN portion offline […]


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