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 1 hour ago·133 stories in the last 24 hours
Can Vision-Language Models Stay Helpful When Facing Implicit Risks? Intent-Privilege OPSD for Efficient Safety-Helpfulness Alignment. It centres on AI Safety, and also names Inference and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Two Conformal Constructions for Adaptive Within-Document AI-Text Screening. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and AI Regulation — the section covering papers, benchmarks, evaluations, interpretability and safety results. Open the original report for the full detail.
CG-HAF: An Interpretable Global-Local Lesion-Burden Fusion Framework for Ordinal Acne Severity Grading in Agentic Skincare Support. It centres on Benchmarks, and also names AI Safety. Reported by arXiv. Bharat Hunt files it under AI Agents — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Diverse Geometries, Frozen Weights: Robust Heterogeneous Treatment-Effect Estimation via Causal Expert Ensembles. It centres on Benchmarks, and also names Phi. Reported by arXiv. Bharat Hunt files it under AI Research and AI Regulation — the section covering papers, benchmarks, evaluations, interpretability and safety results.
When Should LLMs Abstain? Chain-of-Self-Questioning for Selective Risk Control. It centres on Reasoning Models, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and Open Source AI — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Synthesis of Ovarian Cancer Multi-Omics Datasets: A Biology-Informed Evaluation Framework. The story centres on Benchmarks. 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.
ASTOR: Benchmarking and Improving Autoformulation for Soft-Constraint Optimization with a Formal Grammar. It centres on Inference, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and AI Agents — the section covering papers, benchmarks, evaluations, interpretability and safety results.
ECG-SDI: Single-lead Electrocardiogram Enables Continuous Sleep Depth Index Profiling and Scalable Digital Biomarkers for Sleep Health. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Hindsight-Guided Rationale Distillation for Rare Disease Diagnosis. It centres on Reasoning Models, and also names Inference. 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.
OpenAI scraps planned October launch of GPT-6.1 Astra over safety concerns. The story centres on OpenAI. 3 sources have covered it so far, including The Indian Express, The Economic Times and wsj.com. Bharat Hunt files it under AI Models and AI Coding — the section covering a new or updated model, its capabilities, benchmarks or availability.
G$^2$PTQ: Improving LLM Post-Training Quantization with Generalized Gradient Compensation. It centres on AI Safety, and also names GitHub. 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.
EquivSVA: A Formally Verified Dataset of Behavioral Assertions Across Equivalent RTL Implementations. It centres on Benchmarks, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results.
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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.