ghostbuster
Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text
Hans, Abhimanyu, Schwarzschild, Avi, Cherepanova, Valeriia, Kazemi, Hamid, Saha, Aniruddha, Goldblum, Micah, Geiping, Jonas, Goldstein, Tom
Detecting text generated by modern large language models is thought to be hard, as both LLMs and humans can exhibit a wide range of complex behaviors. However, we find that a score based on contrasting two closely related language models is highly accurate at separating human-generated and machine-generated text. Based on this mechanism, we propose a novel LLM detector that only requires simple calculations using a pair of pre-trained LLMs. The method, called Binoculars, achieves state-of-the-art accuracy without any training data. It is capable of spotting machine text from a range of modern LLMs without any model-specific modifications. We comprehensively evaluate Binoculars on a number of text sources and in varied situations. Over a wide range of document types, Binoculars detects over 90% of generated samples from ChatGPT (and other LLMs) at a false positive rate of 0.01%, despite not being trained on any ChatGPT data.
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- Information Technology > Artificial Intelligence > Natural Language > Large Language Model (1.00)
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Ghostbuster: detecting text ghostwritten by large language models
Large language models like ChatGPT write impressively well--so well, in fact, that they've become a problem. Students have begun using these models to ghostwrite assignments, leading some schools to ban ChatGPT. In addition, these models are also prone to producing text with factual errors, so wary readers may want to know if generative AI tools have been used to ghostwrite news articles or other sources before trusting them. What can teachers and consumers do? Existing tools to detect AI-generated text sometimes do poorly on data that differs from what they were trained on.
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Ghostbuster: Detecting Text Ghostwritten by Large Language Models
Verma, Vivek, Fleisig, Eve, Tomlin, Nicholas, Klein, Dan
We introduce Ghostbuster, a state-of-the-art system for detecting AI-generated text. Our method works by passing documents through a series of weaker language models, running a structured search over possible combinations of their features, and then training a classifier on the selected features to predict whether documents are AI-generated. Crucially, Ghostbuster does not require access to token probabilities from the target model, making it useful for detecting text generated by black-box models or unknown model versions. In conjunction with our model, we release three new datasets of human-and AI-generated text as detection benchmarks in the domains of student essays, creative writing, and news articles. We compare Ghostbuster to a variety of existing detectors, including DetectGPT and GPTZero, as well as a new RoBERTa baseline. Ghostbuster achieves 99.0 F1 when evaluated across domains, which is 5.9 F1 higher than the best preexisting model. It also outperforms all previous approaches in generalization across writing domains (+7.5 F1), prompting strategies (+2.1 F1), and language models (+4.4 F1). We also analyze the robustness of our system to a variety of perturbations and paraphrasing attacks and evaluate its performance on documents written by non-native English speakers. Language models such as ChatGPT are capable of producing a wide range of fluent text that closely approximates human language use. However, the proliferation of these models has raised concerns about the authenticity and trustworthiness of text across a variety of domains. For example, fears that students are submitting assignments ghostwritten by language models have led many schools to adapt by restricting the use of ChatGPT in classrooms and homework assignments (Heaven, 2023). Meanwhile, because language models are prone to factual errors and hallucination, readers may desire to know if such tools have been used to ghostwrite news articles or other informative text when deciding whether or not to trust a source.
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VR Assassin's Creed, Stranger Things and Ghostbusters arrive on Meta Quest later this year
Meta announced a slate of upcoming games today for its standalone VR headsets (including the upcoming Meta Quest 3). Apple is expected to enter the virtual headset space next week, so Meta is hoping to make a lasting impression with its lineup of upcoming VR titles from beloved franchises, including Assassin's Creed, Stranger Things, Ghostbusters and Attack on Titan -- along with some VR remakes of old-school classics. In addition to Asgard's Wrath 2, the most enticing game may be the one we know the least about. Although it was little more than a tease, Meta confirmed that Assassin's Creed Nexus VR isn't vaporware after all: The next VR installment in the long-running series will launch in the Meta Quest Store later this year. Unfortunately, further details must wait for its official reveal at Ubisoft Forward on June 12th.
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Welcome to Cat Royale
Have you got questions about Cat Royale? From 22nd March – 2nd April 2023, three cats – Ghostbuster, Pumpkin and Clover – will visit a utopia created by the Blast Theory artists. The cats' every need is catered for. They have dens to curl up in, high platforms to pounce from and curved walls to explore. And at the centre of the room, a robot arm trained by an Artificial Intelligence offers games to make the cats happier. This page is your go to for everything Cat Royale.
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Protecting Autonomous Cars from Phantom Attacks
Early computer vision studies aimed at developing computerized driver intelligence appeared in the mid-1980s when scientists first demonstrated a road-following robot.36 Studies performed from the mid-1980s until 2000 established the fundamentals for automated driver intelligence in related tasks, including detection of pedestrians,39 lanes,3 and road signs.9 However, the vast majority of initial computer vision algorithms aimed at detecting objects required developers to manually program dedicated features. The increase in computational power available in recent years changed the way AI models are created: Features are automatically extracted by training various neural network architectures on raw data. Automatic feature extraction outperformed and replaced the traditional approach of manually programming an object's features.
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'Captain Marvel' Shows How Trolls Lost Their Edge
Captain Marvel's $455 million opening weekend is an enormous, expensive failure. Not for Marvel, or fans of superhero movies, or people whose opinion seems to matter. Trolls have been trying to sabotage Captain Marvel's success since the first trailer dropped last September. So persistent and numerous were these trolls in their "review bombing" that Rotten Tomatoes changed its policies to prevent people from rating a movie before its release, and YouTube altered its search algorithm to uncouple star Brie Larson's name from the smears. Captain Marvel's box office performance has led many to say that the movie "defeated" or "conquered" the trolls--and the trolls certainly did lose.
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Rotten Tomatoes tweaks audience ratings system to thwart online trolls
Walt Disney Co.'s "Captain Marvel" is expected to open with a spectacular $100 million in ticket sales from the U.S. and Canada alone next month. And yet, according to the highly influential website Rotten Tomatoes, only 28% of moviegoers are interested in seeing Marvel Studios' first superhero film with a solo female lead. Blame online trolls, who have previously waged campaigns to lower audience ratings for movies including "Star Wars: The Last Jedi" and "Ghostbusters" by flooding their pages with negative, sometimes sexist comments. Such "review bombing" efforts are a serious problem for Rotten Tomatoes, which depends on credible ratings to drive traffic to its free website. The company, owned by the largest online movie ticket seller, Fandango, now has a plan to curb the abuse.
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Patt Morrison asks: 'The Left Hand of Darkness' author Ursula K. Le Guin
Comic-Con, that massive San Diego convention that spawned an international franchise for fans of sci fi and fantasy comics, films, television and genre books, began in 1970, in the basement of a San Diego hotel. The year before, the singular writer Ursula K. Le Guin had already published the best science fiction novel of the year: "The Left Hand of Darkness," a book not about ray guns or rocket ships, but about other planets, other cultures, other sexualities. As Comic-Con begins yet another flashy fest, one of alternative fiction's true masters -- author of children's books, poetry, novels and nonfiction -- is shaping her forthcoming book, "Words Are My Matter." Worlds too are her subject matter, the deep currents of politics, race, culture, ecology, sexuality -- our own earthly conundrums played out and spun out on alternative worlds. Le Guin's parents were the remarkable Berkeley anthropologists and ethnologists Alfred and Theodora Kroeber, a couple as influential in the field of anthropology as on the imagination of their daughter, and the planets and people of her creation.
The Ghostbusters trashing is just another internet tantrum against change Laurie Penny
We live in a post-mainstream culture. As the way we consume books, movies and television changes, artists and directors no longer need to cater to a "universal" audience viewpoint. This means there is slightly less obligation to pander to what straight white men are supposed to want from culture. Not everyone is happy about that fact, and across the literary and cultural spectrum, tantrums are being thrown. This week the target is the new, all-female Ghostbusters.
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