Reviewerly/exHarmony huggingface dataset:
SPOT! Revisiting Video-Language Models for Event Understanding

Understanding videos is an important research topic for multimodal learning. Leveraging large-scale datasets of web-crawled video-text pairs as weak supervision has become a pre-training paradigm for learning joint representations and showcased remarkable potential in video understanding tasks. However, videos can be multi-event and multi-grained, while these video-text pairs usually contain only broad-level video captions. This raises a question: with such weak supervision, can video representation in video-language models gain the ability to distinguish even factual discrepancies in textual description and understand fine-grained events? To address this, we introduce SPOT Prober, to benchmark existing video-language models's capacities of distinguishing event-level discrepancies as an indicator of models' event understanding ability. Our approach involves extracting events as tuples (<Subject, Predicate, Object, Attribute, Timestamps>) from videos and generating false event tuples by manipulating tuple components systematically. We reevaluate the existing video-language models with these positive and negative captions and find they fail to distinguish most of the manipulated events. Based on our findings, we propose to plug in these manipulated event captions as hard negative samples and find them effective in enhancing models for event understanding.
Innovative Horizons in Aerial Imagery: LSKNet Meets DiffusionDet for Advanced Object Detection

In the realm of aerial image analysis, object detection plays a pivotal role, with significant implications for areas such as remote sensing, urban planning, and disaster management. This study addresses the inherent challenges in this domain, notably the detection of small objects, managing densely packed elements, and accounting for diverse orientations. We present an in-depth evaluation of an object detection model that integrates the Large Selective Kernel Network (LSKNet)as its backbone with the DiffusionDet head, utilizing the iSAID dataset for empirical analysis. Our approach encompasses the introduction of novel methodologies and extensive ablation studies. These studies critically assess various aspects such as loss functions, box regression techniques, and classification strategies to refine the model's precision in object detection. The paper details the experimental application of the LSKNet backbone in synergy with the DiffusionDet heads, a combination tailored to meet the specific challenges in aerial image object detection. The findings of this research indicate a substantial enhancement in the model's performance, especially in the accuracy-time tradeoff. The proposed model achieves a mean average precision (MAP) of approximately 45.7%, which is a significant improvement, outperforming the RCNN model by 4.7% on the same dataset. This advancement underscores the effectiveness of the proposed modifications and sets a new benchmark in aerial image analysis, paving the way for more accurate and efficient object detection methodologies. The code is publicly available at https://github.com/SashaMatsun/LSKDiffDet
Don't forget private retrieval: distributed private similarity search for large language models

While the flexible capabilities of large language models (LLMs) allow them to answer a range of queries based on existing learned knowledge, information retrieval to augment generation is an important tool to allow LLMs to answer questions on information not included in pre-training data. Such private information is increasingly being generated in a wide array of distributed contexts by organizations and individuals. Performing such information retrieval using neural embeddings of queries and documents always leaked information about queries and database content unless both were stored locally. We present Private Retrieval Augmented Generation (PRAG), an approach that uses multi-party computation (MPC) to securely transmit queries to a distributed set of servers containing a privately constructed database to return top-k and approximate top-k documents. This is a first-of-its-kind approach to dense information retrieval that ensures no server observes a client's query or can see the database content. The approach introduces a novel MPC friendly protocol for inverted file approximate search (IVF) that allows for fast document search over distributed and private data in sublinear communication complexity. This work presents new avenues through which data for use in LLMs can be accessed and used without needing to centralize or forgo privacy.
How Capable Can a Transformer Become? A Study on Synthetic, Interpretable Tasks

Transformers trained on huge text corpora exhibit a remarkable set of capabilities, e.g., performing basic arithmetic. Given the inherent compositional nature of language, one can expect the model to learn to compose these capabilities, potentially yielding a combinatorial explosion of what operations it can perform on an input. Motivated by the above, we train autoregressive Transformer models on a synthetic data-generating process that involves compositions of a set of well-defined monolithic capabilities. Through a series of extensive and systematic experiments on this data-generating process, we show that: (1) autoregressive Transformers can learn compositional structures from small amounts of training data and generalize to exponentially or even combinatorially many functions; (2) generating intermediate outputs when composing functions is more effective for generalizing to new, unseen compositions than not generating any intermediate outputs (3) biases in the order of the compositions in the training data result in Transformers that fail to compose some combinations of functions; and (4) the attention layers select which capability to apply while the feed-forward layers execute the selected capability.
Systematic Review Protocol: Requirements Engineering in Quantum Computing

Context: Quantum computing (QC) represents a paradigm shift in computational capabilities, presenting unique challenges in requirements engineering (RE). The complexity of quantum systems and rapid technological advancements necessitate a comprehensive understanding of the current state and future trajectories in RE for QC. Objective: A protocol for carrying out a systematic literature review about the evidence for identifying and analyzing the challenges in RE for QC software. It seeks to evaluate the current methodologies employed in this domain and propose a forward-looking perspective on the evolution of these methodologies to meet future industry and academic needs. Method: This protocol employs a structured approach to search and analyze relevant literature systematically, according to Barbara Kitchenham's guidelines. Results: A validated protocol to conduct a systematic review. The protocol is expected to yield diverse literature spanning theoretical frameworks, empirical studies, and methodological advancements in RE for QC. It will highlight the current challenges, opportunities, and future directions, offering insights into the field's academic and practical aspects. Conclusions: The systematic review aims to provide a nuanced understanding of the RE landscape in QC. It will offer valuable insights for academic researchers, industry professionals, software engineers, industry analysts, and educators, shaping the future discourse in QC development.
Is your vote truly secret? Ballot Secrecy iff Ballot Independence: Proving necessary conditions and analysing case studies

We formalise definitions of ballot secrecy and ballot independence by Smyth, JCS'21 as indistinguishability games in the computational model of security. These definitions improve upon Smyth, draft '21 to consider a wider class of voting systems. Both Smyth, JCS'21 and Smyth, draft '21 improve on earlier works by considering a more realistic adversary model wherein they have access to the ballot collection. We prove that ballot secrecy implies ballot independence. We say ballot independence holds if a system has non-malleable ballots. We construct games for ballot secrecy and non-malleability and show that voting schemes with malleable ballots do not preserve ballot secrecy. We demonstrate that Helios does not satisfy our definition of ballot secrecy. Furthermore, the Python framework we constructed for our case study shows that if an attack exists against non-malleability, this attack can be used to break ballot secrecy.
FuseNet: Self-Supervised Dual-Path Network for Medical Image Segmentation

Semantic segmentation, a crucial task in computer vision, often relies on labor-intensive and costly annotated datasets for training. In response to this challenge, we introduce FuseNet, a dual-stream framework for self-supervised semantic segmentation that eliminates the need for manual annotation. FuseNet leverages the shared semantic dependencies between the original and augmented images to create a clustering space, effectively assigning pixels to semantically related clusters, and ultimately generating the segmentation map. Additionally, FuseNet incorporates a cross-modal fusion technique that extends the principles of CLIP by replacing textual data with augmented images. This approach enables the model to learn complex visual representations, enhancing robustness against variations similar to CLIP's text invariance. To further improve edge alignment and spatial consistency between neighboring pixels, we introduce an edge refinement loss. This loss function considers edge information to enhance spatial coherence, facilitating the grouping of nearby pixels with similar visual features. Extensive experiments on skin lesion and lung segmentation datasets demonstrate the effectiveness of our method. \href{https://github.com/xmindflow/FuseNet}{Codebase.}
Contextual quantum metrology

Quantum metrology promises higher precision measurements than classical methods. Entanglement has been identified as one of quantum resources to enhance metrological precision. However, generating entangled states with high fidelity presents considerable challenges, and thus attaining metrological enhancement through entanglement is generally difficult. Here, we show that contextuality of measurement selection can enhance metrological precision, and this enhancement is attainable with a simple linear optical experiment. We call our methodology "contextual quantum metrology" (coQM). Contextuality is a nonclassical property known as a resource for various quantum information processing tasks. Until now, it has remained an open question whether contextuality can be a resource for quantum metrology. We answer this question in the affirmative by showing that the coQM can elevate precision of an optical polarimetry by a factor of 1.4 to 6.0, much higher than the one by quantum Fisher information, known as the limit of conventional quantum metrology. We achieve the contextuality-enabled enhancement with two polarization measurements which are mutually complementary, whereas, in the conventional method, some optimal measurements to achieve the precision limit are either theoretically difficult to find or experimentally infeasible. These results highlight that the contextuality of measurement selection is applicable in practice for quantum metrology.
Hybrid Sign Language Interpreter Development Using Machine Learning Approach

Sign language even though it has not yet been made into a commercially viable entity has been a boon for deaf-mute people. Many people have been trying to research on how to train in it in an easier and much more effective manner, however at this point such a thing takes a lot resources and time due to which it’s very difficult to make it profitable and fast. The empiricists that are in charge to conduct experiments/exploration in the said field often apply multiple procedures. Commencing in the “collection of data” (it often varies and difficult to choose how to do because), every research team applies a different method or methodology using different methods in order to develop their own approach. Every technique is seen to have its own strength and weak points. The aim of this paper is to research and a good knowledge of all the elements related to speech recognition and image processing so as to further create a platform to iterate and project the meaning of signs. The end goal is the development of a space where people can come together multiple modes of sign language.
تطوير المواد الدراسية لمادة الإملاء للمرحلة الابتدائية الإسلامية في ضوء المدخل التحليلي

Dictation lessons at this school are the additional material, but in the learning process, there are problems, such as the need for more basic books and measurement methods. This is what happens at school ibtidaiyah Al-Anwar Cangringrandu Perak Jombang dan sekolah ibtidaiyah Bahrul Ulum Tambak beras. This study aims to develop a textbook for Madrasah Ibtidaiyyah Al-Anwar and Ibtidaiyyah Bahrul Ulum Jombang to improve writing skills, especially in the field of Imla’ by paying attention to those aspects of knowledge that are needed. The problem of this study is; a form of textbook Imla’developed, The extent to which the effectiveness of Imla’ learning with using textbooks that have been developed. The type of research is the R &amp; D Sugiyono and experiments using the Pree test and post-test on the experimental and control classes. Then to determine the level of effectiveness is the test-T. The results of this study are 1) the development of textbook material dictation for students of Madrasah Ibtidaiyyah Al-Anwar dan Madrasah Ibtidaiyyah Bahrul Ulum Jombang, 2) the development of textbooks that have been prepared, the learning process has increased effectiveness and efficiency. With a value of 16,190476 t count&gt; t-table 3,65 with 99,9%. Confidence level. This means that there is a significant difference between the final value of the initial value.&#x0D; الدرس الاملاء في هذه المدرسة تدخل على المحتوى الاضافي، ولكن في عملية التعلم هناك مشاكل منها عدم الكتاب الأساسي و الطريقة و القياس. والهدف هذا البحث بتطوير المواد الدراسية لمادة الإملاء لتنمية مهارة الكتابة لدى طلاب المدرسة الابتدائية الانوار و مدرسة الابتدائية بحرالعلوم تمباك براس لدى طلاب وباهتمام كفاءة الطلاب واحتياجهم. يحتوي هذا البحث من ثلاثة مباحث: 1) تطوير الكتاب المواد الدراسية لمادة الإملاء على مدرسة الابتدائية الانوار جنكرينج راندو فيراك جومبانج و مدرسة الابتدائية بحرالعلوم تمباك براس جومبانج، 2) فعليه تعليم المواد الدراسية لمادة الإملاء باستخدام الكتابة المطور على مدرسة الابتدائية الانوار جنكرينج راندو فيراك جومبانج و مدرسة الابتدائية بحرالعلوم تمباك براس جومبانج. استخدم الباحث منهج البحث والتطوير بالنموذج الذي اقترحه سوغيونو. استخدم الباحث الاختبار القبلي والاختبار البعدي فى تطوير الكتاب التعليمي ولمعرفة فعالية الكتاب التعليمي. أما نتائج البحث: 1) إن التطوير حصل على الكتاب التعليمي فى مادة الإملاء فى المدرسة الابتدائية الانوار جنكرينج راندو فيراك جومبانج و مدرسة الابتدائية بحرالعلوم تمباك براس، 2) وتدل "ت" حساب 16،190476 أكبر من "ت" جدول 3,65 بجانب الصدق %99,9. هناك الاختلاف ذو معنى بين الاختبار القبلي والاختبار البعدي. والكتاب التعليمي فى مادة الإملاء فعال فى المدرسة الابتدائية الانوار جنكرينج راندو فيراك جومبانج و مدرسة الابتدائية بحرالعلوم تمباك براس جومبانج.
Professional Training in the Field of Information, Library and Archival Affairs at Mariupol State University: Twenty Years of Experience

The purpose of the work is to summarise the experience of training specialists in the field of "Archival Affairs and Information Activities" within the specialty of "Document Studies and Information Activities" at Mariupol State University. The goal is to analyse the effectiveness of the programme, identify the needs for improving the curriculum, and determine the problems faced by students and faculty during the process of mastering this specialisation. The research methodology is based on the principles of scientific objectivity and systematic approach. Historical methods have been applied to establish events relevant to the development of professional training in document studies at Mariupol State University, along with other general scientific methods such as analysis, synthesis, and content analysis of the department's reports. The scientific novelty of the work lies in the generalisation of the history and current state of training professionals in the field of information, library, and archival affairs at Mariupol State University. Conclusions. The training of specialists in the field of "Information, Library, and Archival Affairs" at Mariupol State University takes into account the 20 years of experience of the Information Activities Department, which continues to function in a highly competitive environment due to temporary relocation to Kyiv. Therefore, the dynamics of the development of professional training in document studies at MSU depends on the competitiveness of the proposed educational programmes. The market demand for graduates of the department, the volume and quality of training, the ability to implement a new strategy of internationalisation of MSU, including the introduction of the unique educational and professional programme "Management of Documentation Processes and Development of the Digital Community" from 2023, indicate the potential for further improvement of professional training for document studies. In the foreseeable future, document studies specialists will play an important role in the reintegration of the Mariupol territorial community. &#x0D; Keywords: specialty 029 "Information, Library, and Archival Affairs", records management, higher education, professional training, educational and professional programme, Mariupol State University.&#x0D;
Teaching reading to all learners including those with complex needsBy SarahMosely, Abingdon: Routledge. 2023. ISBN:978‐1‐032‐11475‐0 paperback

Support for LearningEarly View BOOK REVIEW Teaching reading to all learners including those with complex needsBy Sarah Mosely, Abingdon: Routledge. 2023. ISBN:978-1-032-11475-0 paperback Marie Fryer, Corresponding Author Marie Fryer [email protected] Lincoln Saint Christophers Special SchoolSearch for more papers by this author Marie Fryer, Corresponding Author Marie Fryer [email protected] Lincoln Saint Christophers Special SchoolSearch for more papers by this author First published: 24 November 2023 https://doi.org/10.1111/1467-9604.12460Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Early ViewOnline Version of Record before inclusion in an issue RelatedInformation
Algorithms and Software for Numerical Estimation of Posinomial Regression Models Using the Least Squares Method

The article is devoted to the construction of posinomial regression models with several monomes for each input variable. Such models generalize well-known polynomial regressions. Investigated by a posin with one variable and two monomes. The algorithm «A» of approximate estimation of posinomial regressions using the least squares method is proposed. The main disadvantage of the algorithm «A» is that due to the inter-monomic multicollinearity, the estimated posinomial regression may not be consistent with the meaningful meaning of the factors included in it. Therefore, algorithm «B» was developed, which guarantees not only the preservation of the meaningful meaning of the factors, but also the significance of all posinomial regression coefficients according to the Student's t-criterion. Algorithm «B» was implemented in the form of the POSITON-1 software package. The work of the software package is demonstrated by the example of solving a specific applied problem.
Zeros, chaotic ratios and the computational complexity of approximating the independence polynomial

The independence polynomial originates in statistical physics as the partition function of the hard-core model. The location of the complex zeros of the polynomial is related to phase transitions, and plays an important role in the design of efficient algorithms to approximately compute evaluations of the polynomial. In this paper we directly relate the location of the complex zeros of the independence polynomial to computational hardness of approximating evaluations of the independence polynomial. We do this by moreover relating the location of zeros to chaotic behaviour of a naturally associated family of rational functions; the occupation ratios.
ImFusion: Boosting Two-stage 3D Object Detection via Image Candidates

Multi-modal fusion methods combine the advantages of both point clouds and RGB images to boost the performance of 3D object detection. Despite the significant progress, we find that existing two-stage multi-modal fusion methods suffer from the 3D proposal missing in the first stage and projected-style feature fusion mechanism. To solve these problems, we propose a two-stage multi-modal feature fusion network, which improves the recall rate of hard targets in the first stage of network with pseudo 3D proposals generated from image candidates. Then, considering the complementary information between similar image foreground features across multiple objects, we design a multi-modal cross-target fusion module to pay more attention to the foreground objects. It enables a 3D proposal can aggregate the semantic features of multiple image candidates belonging to the same category. Finally, these enhanced fused proposals are processed in the second stage to further boost the performance of 3D detector. Experimental results on SUN RGB-D and KITTI datasets show the effectiveness of our proposed method.
Parents’ Experiences on a Family Literacy Program in Finland

In this article, we investigate a family literacy program called Bedtime Story Shelf, which is an application of lending libraries. In Bedtime Story Shelf-program the families are loaning books from ECE centers and schools to homes. In the study, we present parents’ prior (N = 122) on this program and its relation to families’ prior literacy practises. According to the results, almost all the families took advantage of the Bedtime Story Shelf-activity. However, about half of the families loaned books from the shelf more often. These families also evaluated the activity as more meaningful. They felt that loaning libraries enabled them to expand their knowledge of children’s books and made the children more active in family literacy events. These positive effects did not depend on the prior literacy practises of the family. This means that if we get the families involved in family literacy programs of ECEs and schools, they will find them beneficial. According to the study, one of the key objectives would be motivating the children and involving the parents. Furthermore, the educators should be active and flexible in their attempts to involve all the families.