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AI tool uses face photos to estimate biological age and predict...

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OpenAI’s latest AI model switches languages to Chinese, and other languages...

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ChatGPT is being used by more teens for schoolwork despite its...

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ChatGPT wants to become your reminder app with new ā€˜Tasks’ feature

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Shiba Inu Whales flock to PropiChain because of its AI Innovations...

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OpenAI and The New York Times discuss copyright infringement by AI...

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Brands are experiencing an increase in traffic from ChatGPT

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SEC sues Elon Musk after he allegedly cheated investors out of...

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Allstate accused of paying app makers for driver information in secret

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Nvidia data center customers are delaying Blackwell chip orders because of...

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NVIDIA, Oracle and other US AI chip manufacturers oppose new US...

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Is Automated Hallucination Detection in LLMs Feasible? A Theoretical and Empirical...

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This AI Paper Introduce WebThinker: A Deep Research Agent that Empowers...

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A Step-by-Step Guide to Implement Intelligent Request Routing with Claude

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Researchers from Fudan University Introduce Lorsa: A Sparse Attention Mechanism That...

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Is Automated Hallucination Detection in LLMs Feasible? A Theoretical and Empirical...

Recent advancements in LLMs have significantly improved natural language understanding, reasoning, and generation. These models now excel at diverse tasks like mathematical problem-solving and generating contextually appropriate text. However, a persistent challenge remains: LLMs often generate hallucinations—fluent but factually incorrect responses. These hallucinations undermine the reliability of LLMs, especially...