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.
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3337 stories
A Framework for Context Enrichment and Selective Robustness in LLM Social Agents. 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.
Agentic engineering intelligence with Amazon Nova Multimodal Embeddings and Amazon Bedrock AgentCore. The story centres on Amazon. Reported by AWS. Bharat Hunt files it under AI Agents and AI Models — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Before You Continue: Evaluating Time-Sensitive Safety Awareness in Conversational Assistants. 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.
SecureGARD: Dynamic Ontology-Guided Governance for Secure Tool-Using LLM Agents. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Tools and AI Regulation — the section covering applications people use — assistants, editors, search, productivity.
False Reassurance in LLM Severe-Weather Guidance: A Replayable Evaluation Against Real NWS Alerts. It centres on Benchmarks, and also names Claude. 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.
Who is the Pronoun Pro? Comparing LLMs and Humans at Number-Disambiguation of 'they'. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Optimize the Harness, Not the Model: Fitting a Minimal Agent to a Self-Hostable LLM for Investigative Analysis. The story centres on Claude Code. Reported by arXiv. Bharat Hunt files it under AI Models and AI Tools — the section covering a new or updated model, its capabilities, benchmarks or availability.
ACCT: Asymmetric Cross-LLM Context Transfer. It centres on Inference, 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. Open the original report for the full detail.
SecPO: Principled Adversarial Training for Prompt Injection Security. It centres on Meta, and also names Benchmarks and GitHub. Reported by arXiv. Bharat Hunt files it under AI Agents — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
When Does Test-Time Search Help World Action Models? An Empirical Audit of Candidate Selection and Simulator Integrity. It centres on Inference, and also names 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.
Beyond Words Alone: Disentangling Distributed Evidence for Visually Grounded Cultural Translation. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Moonshot curbs hacking ability in new Kimi model as fears grow over AI-powered cyberattacks. The story centres on Moonshot AI. The Economic Times and The Indian Express have both covered it. Bharat Hunt files it under AI Models and Open Source AI — the section covering a new or updated model, its capabilities, benchmarks or availability.
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.