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

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Are We Ready for Multi-Image Reasoning? Launching VHs: The Visual Haystacks...

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Natural Language Processing

Small language models: 10 Breakthrough Technologies 2025

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Unlock the Future: AI Agents and LLMs at Chatbot Conference 2024

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Google DeepMind at NeurIPS 2024

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How to Evaluate Jailbreak Methods: A Case Study with the StrongREJECT...

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Into The Weeds of Artificial Intelligence

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Introducing Gemini 2.0: our new AI model for the agentic era

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Why ā€˜Beating China’ in AI Brings Its Own Risks

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AI means the end of internet search as we’ve known it

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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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AI Observer

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...