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.
Ingestion is behind — last completed run was 11 hours ago.
News ingestion is temporarily unavailable.
The pipeline has not completed a run recently, so what is below may be behind. Nothing here is ever filled in with placeholder news.
5345 stories
APEX-Harm: Evaluating Agent Safety in Shared Professional Workspaces. It centres on Benchmarks, and also names Model Context Protocol and Gemini. Reported by arXiv. Bharat Hunt files it under AI Models and AI Agents — the section covering a new or updated model, its capabilities, benchmarks or availability.
Language-Specific Effects of Tokenizer Choice in Multilingual Language Models. Reported by arXiv. Bharat Hunt files it under AI Models and AI Funding — the section covering a new or updated model, its capabilities, benchmarks or availability. Open the original report for the full detail.
Rehearse Everything, Remember Nothing: Attic-KV Rehearses What Will Be Read. The story centres on Nothing. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
A persistent accuracy ceiling in automated verbal deception detection. It centres on Meta, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
All Verdicts are Not Equal: Rethinking LLM Judge Reliability. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
ILM: An AI-Powered Storytelling Educational Tool. Reported by arXiv. Bharat Hunt files it under AI Tools — the section covering applications people use — assistants, editors, search, productivity. Open the original report for the full detail.
When Should Agents Think? Adaptive Reasoning via Cross-Turn Estimation. It centres on Fine-tuning, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Natural Language to First-Order Logic LLM-based Autoformalization. It centres on Benchmarks, and also names Fine-tuning. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results. Open the original report for the full detail.
InterviewPlayground: A Simulation Environment for Evaluating AI Interviewers. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results. Open the original report for the full detail.
Examining Social Attribution in LLM Reasoning: A Theory-Guided Probing Methodology. It centres on Benchmarks, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
How assigned AI use before class shapes active student engagement in class. Reported by arXiv. Bharat Hunt files it under AI Research and AI Tools — the section covering papers, benchmarks, evaluations, interpretability and safety results. Open the original report for the full detail.
FoldBack: Self-Correcting Masked Generative Policy for Long-Horizon Garment Folding. The story centres on Inference. Reported by arXiv. Bharat Hunt files it under AI Regulation and Robotics — the section covering law, policy, courts, standards and government positions on AI.
Bharat Hunt links to original reporting and does not republish it. Headlines and links belong to their publishers; summaries and the trend ranking are ours. All AI stories
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.