The latest AI news, launches, models, companies and research — collected from official sources, research feeds and reporting, grouped into stories and ranked by the BharatHunt Trend Score.
Updated 2 hours ago116 stories in the last 24 hours
59 stories
Agent World Model in the Wild: Computer-Use Agent Environment Synthesis. It centres on Model Context Protocol, and also names GPT and Qwen. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Models — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Stale-Document Poisoning: When Outdated Retrieval Overrides Correct Model Answers. It centres on RAG, and also names AI Safety and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models and AI Research — the section covering a new or updated model, its capabilities, benchmarks or availability.
SemanticFold: Latent Sequence Compression SeparatesLanguage Modeling, Decodability, and Reasoning. It centres on Inference, and also names Qwen. Reported by arXiv. Bharat Hunt files it under AI Models and AI Research — the section covering a new or updated model, its capabilities, benchmarks or availability.
PHYRD: A Living Benchmark for Reproducing and Extending Theoretical Physics Research. It centres on Benchmarks, and also names OpenAI and Qwen. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
When Victorian Becomes a Prompt: Literary Periodization as a Generative Constraint in 100 AI-Generated Novels. It centres on GPT, and also names Qwen and Llama. Reported by arXiv. Bharat Hunt files it under AI Models and Generative AI — the section covering a new or updated model, its capabilities, benchmarks or availability.
MuninAI: A Self-Hosted Agentic Framework for Independent Research Groups. It centres on Benchmarks, and also names Qwen and GPT. Reported by arXiv. Bharat Hunt files it under AI Research and Open Source AI — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Decision-Oriented Recommendation Reranking: An Empirical Study of Jev. It centres on Qwen, and also names Amazon. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Navigating the digital spectrum: Assessing political bias, stability, and downstream fairness in Large Language Models. It centres on Benchmarks, and also names Gemma and Qwen. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Beyond the Benchmark: Conditioning, Domains and Failure Modes of Qwen3-TTS. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models and AI Research — the section covering a new or updated model, its capabilities, benchmarks or availability.
Decodable but Misrouted: Sparse Features Uncover a Readout Gap in Vision-Language Models for Harmful Meme Detection. It centres on Gemma, and also names Benchmarks and Qwen. Reported by arXiv. Bharat Hunt files it under AI Models and AI Coding — the section covering a new or updated model, its capabilities, benchmarks or availability.
Evaluating Sycophancy in Chinese Large Language Models on Factual Questions Derived from Online Search Queries. It centres on DeepSeek, and also names Qwen and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
MultiInpaintCOCO: Fine-Grained Visual Understanding in Multiple Languages. It centres on Benchmarks, and also names Multimodal and Gemma. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
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Stories in the last 24 hours, against the 24 before it. A change is shown only where the earlier window had enough coverage to compare against.
Our own 0-100 ranking, not an industry metric and not anyone else’s “trending” number. It combines how recently a story was covered (32%), how many independent publications covered it (28%), how fast that coverage is arriving right now (20%), how reliable those sources are (12%) and how many people opened the story (8%).
A story we cannot date carries no score at all rather than a made-up one, so some cards show no badge. Summaries are written by Bharat Hunt from the headline and the coverage — the original article is always the source of truth, and every link goes to the publisher.