Cream: Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models

Advances in Large Language Models (LLMs) have inspired a surge of research exploring their expansion into the visual domain. While recent models exhibit promise in generating abstract captions for images and conducting natural conversations, their performance on text-rich images leaves room for improvement. In this paper, we propose the Contrastive Reading Model (Cream), a novel neural architecture designed to enhance the language-image understanding capability of LLMs by capturing intricate details typically overlooked by existing methods. Cream integrates vision and auxiliary encoders, complemented by a contrastive feature alignment technique, resulting in a more effective understanding of textual information within document images. Our approach, thus, seeks to bridge the gap between vision and language understanding, paving the way for more sophisticated Document Intelligence Assistants. Rigorous evaluations across diverse tasks, such as visual question answering on document images, demonstrate the efficacy of Cream as a state-of-the-art model in the field of visual document understanding. We provide our codebase and newly-generated datasets at https://github.com/naver-ai/crea

Invigorating Care Farm Ecosystem Based on Public Service Innovation: Case of South Korea

Recently, the importance of care farming has been emphasized worldwide for the purpose of public health and healing, and, in particular, discussions on innovative transformation and expansion of the care farm ecosystem have continued in terms of convergence of agriculture and welfare. This study aims to present influencing factors based on a hierarchical concept framework for revitalizing care farm ecosystem based on public service innovation. To this end, the AHP methodology was used. Through previous studies, 16 variables were derived within four categories: recognition, structure, leadership, process, and recognition of variables that affect the activation of the care farm ecosystem and conceptualized them through Delphi techniques. In addition, a survey was conducted on 28 stakeholders in care farming to derive the importance of each variable. As a result of the analysis, ‘reliability’ was derived as the most important factor, followed by factors such as human competence, vision, civic participation, and innovation awareness. Hence, it was confirmed that trust and communication between stakeholders are important to lead the innovative public service ecosystem of care farm, and above all, human competence is an important influencing factor

On the Security of Practical Mail User Agents against Cache Side-Channel Attacks

Mail user agent (MUA) programs provide an integrated interface for email services. Many MUAs support email encryption functionality to ensure the confidentiality of emails. In practice, they encrypt the content of an email using email encryption standards such as OpenPGP or S/MIME, mostly implemented using GnuPG. Despite their widespread deployment, there has been insufficient research on their software structure and the security dependencies among the software components of MUA programs. In order to understand the security implications of the structures and analyze any possible vulnerabilities of MUA programs, we investigated a number of MUAs that support email encryption. As a result, we found severe vulnerabilities in a number of MUAs that allow cache side-channel attacks in virtualized desktop environments. Our analysis reveals that the root cause originates from the lack of verification and control over the third-party cryptographic libraries that they adopt. In order to demonstrate this, we implemented a cache side-channel attack on RSA in GnuPG and then conducted an evaluation of the vulnerability of 13 MUAs that support email encryption in Ubuntu 14.04, 16.04 and 18.04. Based on our experiment, we found that 10 of these MUA programs (representing approximately 77% of existing MUA programs) allow the installation of a vulnerable version of GnuPG, even when the latest version of GnuPG, which is secure against most cache side-channel attacks, is in use. In order to substantiate the importance of the vulnerability we discovered, we conducted a FLUSH+RELOAD attack on these MUA programs and demonstrated that the attack restored 92% of the bits of the 2048-bit RSA private key when the recipients read a single encrypted email

DEVELOPMENT OF LEAD SLOWING DOWN SPECTROMETER FOR ISOTOPIC FISSILE ASSAY

A lead slowing down spectrometer (LSDS) is under development for analysis of isotopic fissile material contents in pyro-processed material, or spent fuel. Many current commercial fissile assay technologies have a limitation in accurate and direct assay of fissile content. However, LSDS is very sensitive in distinguishing fissile fission signals from each isotope. A neutron spectrum analysis was conducted in the spectrometer and the energy resolution was investigated from 0.1eV to 100keV. The spectrum was well shaped in the slowing down energy. The resolution was enough to obtain each fissile from 0.2eV to lkeV. The detector existence in the lead will disturb the source neutron spectrum. It causes a change in resolution and peak amplitude. The intense source neutron production was designed for similar to E12 n's/sec to overcome spent fuel background. The detection sensitivity of U238 and Th232 fission chamber was investigated. The first and second layer detectors increase detection efficiency. Thorium also has a threshold property to detect the fast fission neutrons from fissile fission. However, the detection of Th232 is about 76% of that of U238. A linear detection model was set up over the slowing down neutron energy to obtain each fissile material content. The isotopic fissile assay using LSDS is applicable for the optimum design of spent fuel storage to maximize burnup credit and quality assurance of the recycled nuclear material for safety and economics. LSDS technology will contribute to the transparency and credibility of pyro-process using spent fuel, as internationally demanded.close0

Ablation laser fluence as an effective parameter to control superconductivity in Ba1−xKxBiO3 films

Potassium doping in insulating BaBiO3 induces superconductivity, with high superconducting transition temperatures, Tc, of up to 31 K in bulk. We investigated growth control of superconducting properties of BKBO films, by varying laser fluence using pulsed laser deposition technique. As cation stoichiometry, especially potassium concentration in BKBO films, was sensitively changed with laser fluence, we were able to precisely control Tc of BKBO films. Following the trend of the bulk phase diagram, Tc showed the highest value of 24.5 ± 0.5 K at the optimal stoichiometry. This result can provide optimal guidance for the synthesis of high-quality BKBO films, and demonstrates the effectiveness of laser fluence to study emerging superconducting phenomena in PLD-grown complex oxide thin films. © 2017 Elsevier B.V