Global existence of solutions for the Hall-MHD equations

In this paper, we study the global well-posedness of the incompressible Hall-MHD system for small initial data $( u_0, b_0) \in \dot B^{\frac3p -1}_{p,5} (\mathbb{R}) \times \Big( \dot B^{\frac3p -1}_{p,5} (\mathbb{R}) \cap \dot B^{\frac3p}_{p,1}(\mathbb{R}) \Big)$ for $1 < p < 5$. We get the result under the weaker regularity and integrability conditions of the initial data than the previous works. We also give integral formulae for the solution

LMCanvas: Object-Oriented Interaction to Personalize Large Language Model-Powered Writing Environments

Large language models (LLMs) can enhance writing by automating or supporting specific tasks in writers' workflows (e.g., paraphrasing, creating analogies). Leveraging this capability, a collection of interfaces have been developed that provide LLM-powered tools for specific writing tasks. However, these interfaces provide limited support for writers to create personal tools for their own unique tasks, and may not comprehensively fulfill a writer's needs -- requiring them to continuously switch between interfaces during writing. In this work, we envision LMCanvas, an interface that enables writers to create their own LLM-powered writing tools and arrange their personal writing environment by interacting with "blocks" in a canvas. In this interface, users can create text blocks to encapsulate writing and LLM prompts, model blocks for model parameter configurations, and connect these to create pipeline blocks that output generations. In this workshop paper, we discuss the design for LMCanvas and our plans to develop this concept.Comment: Accepted to CHI 2023 Workshop on Generative AI and HC

Strategies Used by Patentees to Delay Patent Disclosure in Literature Searches and Measures for Counteracting Them

65-75In the context of today’s knowledge-based economy, in which creation, distribution, use, and accumulation of information are the primary forces driving wealth and jobs, intellectual property rights represent an important arrangement between the inventor and the government through which the former is granted strong protections by the latter in exchange for “disclosure” to the general public upon expiration of the legally determined protection period. The ultimate goal of such an arrangement is to promote inventions, thereby supporting industrial progress. In accord with this, under the patent system, disclosure of the information related to the patented invention is the prerequisite for obtaining the exclusive right to a novel technology. However, using the loophole provided by the cost-intensive and time-consuming process of analyzing the exponentially increasing patent documentation required around the world, an increasing number of firms try to maintain a competitive advantage by drafting their patent documents in a manner allowing the delay of their actual public disclosure. The current study investigated actual cases of strategies for delaying public disclosure of patents used by some companies when drafting patent documents, and discusses possible measures for more efficient mining of patent literature and related institutional improvement to address this issue

ECCV Caption: Correcting False Negatives by Collecting Machine-and-Human-verified Image-Caption Associations for MS-COCO

Image-Text matching (ITM) is a common task for evaluating the quality of Vision and Language (VL) models. However, existing ITM benchmarks have a significant limitation. They have many missing correspondences, originating from the data construction process itself. For example, a caption is only matched with one image although the caption can be matched with other similar images, and vice versa. To correct the massive false negatives, we construct the Extended COCO Validation (ECCV) Caption dataset by supplying the missing associations with machine and human annotators. We employ five state-of-the-art ITM models with diverse properties for our annotation process. Our dataset provides x3.6 positive image-to-caption associations and x8.5 caption-to-image associations compared to the original MS-COCO. We also propose to use an informative ranking-based metric, rather than the popular Recall@K(R@K). We re-evaluate the existing 25 VL models on existing and proposed benchmarks. Our findings are that the existing benchmarks, such as COCO 1K R@K, COCO 5K R@K, CxC R@1 are highly correlated with each other, while the rankings change when we shift to the ECCV mAP. Lastly, we delve into the effect of the bias introduced by the choice of machine annotator. Source code and dataset are available at https://github.com/naver-ai/eccv-captionComment: 30 pages (1.7MB); Source code and dataset are available at https://github.com/naver-ai/eccv-caption; v2 fixes minor typo

Beyond Fact Verification: Comparing and Contrasting Claims on Contentious Topics

As the importance of identifying misinformation is increasing, many researchers focus on verifying textual claims on the web. One of the most popular tasks to achieve this is fact verification, which retrieves an evidence sentence from a large knowledge source such as Wikipedia to either verify or refute each factual claim. However, while such problem formulation is helpful for detecting false claims and fake news, it is not applicable to catching subtle differences in factually consistent claims which still might implicitly bias the readers, especially in contentious topics such as political, gender, or racial issues. In this study, we propose ClaimDiff, a novel dataset to compare the nuance between claim pairs in both a discriminative and a generative manner, with the underlying assumption that one is not necessarily more true than the other. This differs from existing fact verification datasets that verify the target sentence with respect to an absolute truth. We hope this task assists people in making more informed decisions among various sources of media

Broadband epsilon-near-zero and epsilon-near-pole 1D nanograting metamaterials in near-infrared regimesI

In this study, we investigate broadband absorption using epsilon-near-zero (ENZ) and epsilon-near-pole (ENP) properties of indium tin oxide (ITO) 1D nanograting hyperbolic metamaterials (HMMs)