Search results
1 day ago · A comprehensive review of the current research on the application of Large Language Models in cybersecurity, using a systematic literature review (SLR) to synthesize key findings on how LLMs have been employed in tasks such as vulnerability detection, malware analysis, and phishing detection. The rapid evolution of artificial intelligence (AI), particularly Large Language Models (LLMs) such as GPT-3 and BERT, has transformed various domains by enabling sophisticated natural language ...
2 days ago · This blog post offers a comparative analysis of Felo AI Academic Search and Semantic Scholar, highlighting the unique features and strengths of each platform. Felo AI provides multilingual capabilities, AI-generated answers with citations, mind map creation, simplified explanations, PPT generation, and personalized research management. Semantic Scholar offers AI-powered summaries (TLDRs), research feeds, a semantic reader, and a comprehensive database. Both platforms enhance academic ...
4 days ago · From the website: "Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI." Research Rabbit. Research Rabbit blends the capabilities of Semantic Scholar with Zotero integration, citation visualizations, and tools to share research with colleagues. LitMaps.
4 days ago · The idea that human cognition is, or can be understood as, a form of computation is a useful conceptual tool for cognitive science. It was a foundational assumption during the birth of cognitive science as a multidisciplinary field, with Artificial Intelligence (AI) as one of its contributing fields. One conception of AI in this context is as a provider of computational tools (frameworks, concepts, formalisms, models, proofs, simulations, etc.) that support theory building in cognitive ...
6 days ago · Semantic Scholar — a free, AI-powered research tool for scientific literature, which supplies underlying data for many of the other tools on this list) provides brief summaries ('TLDR's) of the main objectives and results of papers.
5 days ago · In this paper, we investigate the semantic clustering properties of deep reinforcement learning (DRL) for video games, enriching our understanding of the internal dynamics of DRL and advancing its interpretability. In this context, semantic clustering refers to the inherent capacity of neural networks to internally group video inputs based on semantic similarity. To achieve this, we propose a novel DRL architecture that integrates a semantic clustering module featuring both feature ...
4 days ago · Accounting for the value of semantic interoperability in interdisciplinary research, such as that of environmental sciences, an extensive collection and analysis of existing semantic artefacts in ...
