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The author fact-checks their previous post on NeurIPS 2026 position track decisions and Pangram AI detection, correcting earlier errors and providing updated benchmarks and reports.
The author argues against dismissing articles based on AI authorship, stating that the use of AI does not invalidate the content's points and urging engagement with the arguments instead.
The paper introduces SlopShape, a method to identify AI-generated commercial web content by analyzing structural features, achieving 98% macro-F1 accuracy and enabling attribution to specific AI models.
An interactive game that challenges users to distinguish AI-generated images from real photographs within a 60-second time limit.
A tweet discusses an AI-written article on WeChat that examines Hai Zi's royalty income and its connection to Qian Xuesen, highlighting the bizarre era of the 1980s.
Pangram is an AI detector tool that accurately identifies AI-generated text and images, validated by third-party research and used by institutions worldwide.
The article critiques AI detection tools for relying on surface-level patterns that can misidentify human writing, especially when polished, and highlights their failure to capture the unique voice of individual writers.
The article discusses an incident where David Sacks' tweet was detected as AI-generated by Pangram, sparking debate about AI detectors, and includes an experiment using an LLM to mimic human writing.
The article critiques Google's ad review process for allowing deceptive ads on platforms like YouTube, and proposes using AI models like Gemini to improve detection and enforcement of advertising policies.
A free browser-based image forensics tool that analyzes photos for signs of editing, AI generation, and other artifacts without uploading files, ensuring user privacy.
Instagram's AI detection system is erroneously labeling non-AI-generated images, causing user confusion and mistrust, while actual AI content often escapes labeling. Meta's methods remain unclear, and tools like Canva have contributed to the issue.
The article argues that watermarking may fail in agentic AI contexts because the final output often involves editing, making the text non-contiguous and disrupting watermark detection.
AI-generated menus in restaurants often look unnatural and similar due to generative models trained on narrow datasets, leading to aesthetic convergence and issues with content quality and detection.
This article introduces a tool that uses C2PA standards to verify if files were created or processed with Anthropic's Claude AI, ensuring privacy by not storing uploaded files.
The article explores the challenges of AI detection, featuring Pangram's startup efforts, including a $9 million funding round and a partnership with Substack to identify AI-generated content.
In a TechCrunch podcast, Pangram's CEO Max Spero warns that the internet is dangerously close to the dead internet theory becoming reality due to AI-generated content, while discussing their AI detection tools and recent $9M funding.
The article explores Pangram, an AI startup that detects AI-generated text, its role in publishing scandals, and questions about the trustworthiness of its detection model.
This paper introduces interpretable form-level features to detect and guide LLM-generated Korean poetry, achieving improved detection accuracy and generating poems that more closely resemble human writing in form.
An MIT report strongly advises against relying on AI detectors, citing risks such as arms races with AI humanizers, false positives harming students, and unfair impacts on non-native English speakers and neurodivergent individuals.
This tweet criticizes the trend of people inventing personal methods to detect AI-generated text, noting that common writing techniques like lists of three are often incorrectly used as indicators.