Predicting protein function and structure from sequence is one important challenge for computational biology. For 26 years, most state-of-the-art approaches combined machine learning evolutionary information. However, some applications retrieving related proteins becoming too time-consuming. Additionally, information less powerful small families, e.g. the Dark Proteome. Both these problems are addressed by new methodology introduced here.We a novel way to represent sequences as continuous...

Conversational interfaces recently gained a lot of attention. One the reasons for current hype is fact that chatbots (one particularly popular form conversational interfaces) nowadays can be created without any programming knowledge, thanks to different toolkits and so-called Natural Language Understanding (NLU) services. While these NLU services are already widely used in both, industry science, so far, they have not been analysed systematically. In this paper, we present method evaluate...

Over the last two decades, agile methods have transformed and brought unique changes to software development practice by strongly emphasizing team collaboration, customer involvement, change tolerance. The success of for small, co-located teams has inspired organizations increasingly apply practices large-scale efforts. Since these are originally designed small teams, unprecedented challenges occur when introducing them at larger scale, such as inter-team coordination communication,...

Decentralized identifiers and verifiable credentials have been proposed as a self-sovereign privacy-friendly alternative to centralized proprietary authentication services. Currently, W3C standard exists that attempts unify existing proposals find common layer for decentralized identification verification. However, there are some limitations of in comparison established, centrally controlled platforms concerning trust, privacy usability. In this paper, we first describe all workflows which...

Keyphrase extraction is the process of automatically selecting a small set most relevant phrases from given text.Supervised keyphrase approaches need large amounts labeled training data and perform poorly outside domain (Bennani-Smires et al., 2018).In this paper, we present PatternRank, which leverages pretrained language models part-of-speech for unsupervised single documents.Our experiments show PatternRank achieves higher precision, recall F 1 -scores than previous state-of-the-art...

Text classification of unseen classes is a challenging Natural Language Processing task and mainly attempted using two different types approaches. Similarity-based approaches attempt to classify instances based on similarities between text document representations class description representations. Zero-shot aim generalize knowledge gained from training by assigning appropriate labels unknown documents. Although existing studies have already investigated individual these categories, the...

This study describes the roles of architects in scaling agile frameworks with help a structured literature review. We aim to provide primary analysis 20 identified frameworks. Subsequently, we thoroughly describe three popular frameworks: Scaled Agile Framework, Large Scale Scrum, and Disciplined 2.0. After specifying main concepts frameworks, characterize enterprise, software, solution, information architects, as four Finally, discussion generalizable findings on role

Abstract Background One common task in Computational Biology is the prediction of aspects protein function and structure from their amino acid sequence. For 26 years, most state-of-the-art approaches toward this end have been marrying machine learning evolutionary information. The retrieval related proteins ever growing sequence databases becoming so time-consuming that analysis entire proteomes becomes challenging. On top, information less powerful for small families, e.g. Dark Proteome ....

In today's assistant landscape, personalisation enhances interactions, fosters long-term relationships, and deepens engagement. However, many systems struggle with retaining user preferences, leading to repetitive requests disengagement. Furthermore, the unregulated opaque extraction of preferences in industry applications raises significant concerns about privacy trust, especially regions stringent regulations like Europe. response these challenges, we propose a memory system for voice...

Like any digital certificate, Verifiable Credentials (VCs) require a way to revoke them in case of an error or key compromise. Existing solutions for VC revocation, most prominently Bitstring Status List, are not viable many use cases since they leak the issuer's behavior, which turn leaks internal business metrics. For instance, exact staff fluctuation through issuance and revocation employee IDs. We introduce CRSet, mechanism that allows issuer encode information years worth VCs as Bloom...

Over recent years, the blockchain ecosystem has grown significantly with emergence of new Layer-1 (L1) and Layer-2 (L2) networks. These blockchains typically host Decentralized Exchanges (DEXes) for trading assets such as native currencies stablecoins. While this diversity enriches ecosystem, it also fragments liquidity, posing challenges DEXes offering same across multiple blockchains. This fragmentation leads to price discrepancies, creating opportunities like arbitrages profit-seeking...

The field of text privatization often leverages the notion $\textit{Differential Privacy}$ (DP) to provide formal guarantees in rewriting or obfuscation sensitive textual data. A common and nearly ubiquitous form DP application necessitates addition calibrated noise vector representations text, either at data- model-level, which is governed by privacy parameter $\varepsilon$. However, almost undoubtedly leads considerable utility loss, thereby highlighting one major drawback NLP. In this...

Lexical Substitution is the task of replacing a single word in sentence with similar one. This should ideally be one that not necessarily only synonymous, but also fits well into surrounding context target word, while preserving sentence's grammatical structure. Recent advances have leveraged masked token prediction Pre-trained Language Models to generate replacements for given sentence. With this technique, we introduce ConCat, simple augmented approach which utilizes original bolster...

Retrieval-augmented generation (RAG) has emerged as an approach to augment large language models (LLMs) by reducing their reliance on static knowledge and improving answer factuality. RAG retrieves relevant context snippets generates based them. Despite its increasing industrial adoption, systematic exploration of components is lacking, particularly regarding the ideal size provided context, choice base LLM retrieval method. To help guide development robust systems, we evaluate various...

Fact verification (FV) aims to assess the veracity of a claim based on relevant evidence. The traditional approach for automated FV includes three-part pipeline relying short evidence snippets and encoder-only inference models. More recent approaches leverage multi-turn nature LLMs address as step-by-step problem where questions inquiring additional context are generated answered until there is enough information make decision. This iterative method makes process rational explainable. While...