Incorporating external context can significantly enhance the response quality of Large Language Models (LLMs). However, real-world contexts often mix relevant information with disproportionate inappropriate content, posing reliability risks. How do LLMs process and prioritize mixed context? To study this, we introduce the Poisoned Context Testbed, pairing queries with real-world contexts containing relevant and inappropriate content. Inspired by associative learning in animals, we adapt the Rescorla-Wagner (RW) model from neuroscience to quantify how competing contextual signals influence LLM outputs. Our adapted model reveals a consistent behavioral pattern: LLMs exhibit a strong tendency to incorporate information that is less prevalent in the context. This susceptibility is harmful in real-world settings, where small amounts of inappropriate content can substantially degrade response quality. Empirical evaluations on our testbed further confirm this vulnerability. To tackle this, we introduce RW-Steering, a two-stage finetuning-based approach that enables the model to internally identify and ignore inappropriate signals. Unlike prior methods that rely on extensive supervision across diverse context mixtures, RW-Steering generalizes robustly across varying proportions of inappropriate content. Experiments show that our best fine-tuned model improves response quality by 39.8% and reverses the undesirable behavior curve, establishing RW-Steering as a robust, generalizable context engineering solution for improving LLM safety in real-world use.

For years, conservative media, lawmakers and talking heads have been sounding the alarm about President Joe Biden's cognitive free fall. And for years, left-wing media, lawmakers and their loyal mouthpieces waved it off with the same condescending dismissal -- accusing us of lying, fear-mongering or worse. Some even went so far as to say they couldn't keep up with Biden's supposed brilliance and jam-packed schedule of what was mostly just one morning briefing and two mid-afternoon naps. Now that Biden has shuffled out of office, left-wing media seems to be waking up to the glaringly obvious. The New York Times of all places -- yes, the same paper that acted as Biden's PR firm -- has revealed that he relied on teleprompters during intimate fundraisers in private homes.

Presidents Clinton, George H.W. Bush, Obama, Biden and Trump all pay respect to Jimmy Carter at his state funeral in Washington, D.C.. During the 2024 campaign cycle, Americans witnessed what appeared to be no love lost between President-elect Donald Trump and former President Barack Obama. However, at former President Jimmy Carter's funeral the two recent presidents appeared to be enjoying each other's company and largely ignored other dignitaries arriving around them, including Vice President Kamala Harris and President Biden. Susan Constantine, a communication and body language expert, said Harris came off "as cool as could be." When she was walking she was very robotic.

To understand a narrative, it is essential to comprehend the temporal event flows, especially those associated with main characters; however, this can be challenging with lengthy and unstructured narrative texts. To address this, we introduce NECE, an open-access, document-level toolkit that automatically extracts and aligns narrative events in the temporal order of their occurrence. Through extensive evaluations, we show the high quality of the NECE toolkit and demonstrates its downstream application in analyzing narrative bias regarding gender. We also openly discuss the shortcomings of the current approach, and potential of leveraging generative models in future works. Lastly the NECE toolkit includes both a Python library and a user-friendly web interface, which offer equal access to professionals and layman audience alike, to visualize event chain, obtain narrative flows, or study narrative bias.

Some of today's tech giants believe that artificial intelligence (AI) should be more widely utilized. If Tesla's Elon Musk delivers on his promise of offering true self-driving cars (and by extension, delivery trucks) and they become widely available within the next decade, then what's going to happen to those millions of people? A major breakthrough on this front occurred in 2015 when a bot named Eugene Goostman became the first computer to pass the Turing test. Human dominance is not due to strong muscles and sharp teeth but rather intelligence and ingenuity. We can defeat stronger, bigger and faster animals because we're able to create and use physical and cognitive tools to control them.

Large, AI-powered language models (LLMs) like OpenAI's GPT-3 have enormous potential in the enterprise. For example, GPT-3 is now being used in over 300 apps by thousands of developers to produce more than 4.5 billion words per day. And Naver, the company behind the eponymous search engine Naver, is employing LLMs to personalize search results on the Naver platform -- following on the heels of Bing and Google. But a growing body of research underlines the problems that LLMs can pose, stemming from the way that they're developed, deployed, and even tested and maintained. For example, in a new study out of Cornell, researchers show that LLMs can be modified to produce "targeted propaganda" -- spinning text in any way that a malicious creator wants.

President Barack Obama bumped fists with Nathan Copeland during a tour of innovation projects at the White House Frontiers Conference at the University of Pittsburgh in 2016. President Barack Obama bumped fists with Nathan Copeland during a tour of innovation projects at the White House Frontiers Conference at the University of Pittsburgh in 2016. A robotic arm with a sense of touch has allowed a man who is paralyzed to quickly perform tasks like pouring water from one cup into another. The robotic arm provides tactile feedback directly to the man's brain as he uses his thoughts to control the device, a team reports Thursday in the journal Science. Previous versions of the arm required the participant, Nathan Copeland, to guide the arm using vision alone.

Samuel Greengard is an author and journalist based in West Linn, OR, USA.

Being born without fingers can be tough for any child. Getting new ones - especially red and blue superhero themed digits - has made 8-year-old Kaori Misue a vibrant playground star. Flexing her wrist muscles to bend the plastic fingers, she can work with tape and stickers at an arts and crafts class. She can ride a bike, skip a rope and bake pastries with her mom. Misue has a brand new prosthetic hand thanks to the genius of 21-year-old inventor Gino Tubaro and his 3D printer.

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