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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875 stories
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.
BiasFlow: Geometric Monitoring and Backbone Regularization for Spurious Feature Reliance. It centres on Reliance Jio, and also names AI Safety and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and AI Tools, and tracks it as India coverage — the section covering papers, benchmarks, evaluations, interpretability and safety results.
CLIMB: Confidence-Guided Complementary Evidence for Multimodal Retrieval-Augmented Generation. It centres on Multimodal, and also names RAG and Inference. 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.
Towards Mitigating Fabricated Consensus: The Active Provenance Gate for Multi-Agent Debate Synthesis. Reported by arXiv. Bharat Hunt files it under AI Research and AI Agents — the section covering papers, benchmarks, evaluations, interpretability and safety results. Open the original report for the full detail.
Learning to Ideate for Scientific Impact. The story centres on Fine-tuning. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results. Open the original report for the full detail.
Benchmarking the Explanatory Quality of Open-Weight Vision-Language Models in Face Recognition. It centres on Benchmarks, and also names Reliance Jio and AI Safety. Reported by arXiv. Bharat Hunt files it under Open Source AI and AI Research, and tracks it as India coverage — the section covering open-weight models, permissive licences and community releases.
Decoupling Patient Personas and Clinical Workflows: A Dual-Agent Approach to Realistic Medical Dialogue Generation. It centres on AI Safety, and also names Fine-tuning. Reported by arXiv. Bharat Hunt files it under AI Regulation and AI Agents — the section covering law, policy, courts, standards and government positions on AI.
From Reactive Containment to Proactive Assurance: Lessons from OpenAI, Anthropic, and Google Agent Security Incidents. It centres on OpenAI, and also names Anthropic and Google. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Aligning Multimodal Patient Evidence with Biomedical Knowledge Graphs for Clinical LLMs. It centres on Multimodal, and also names AI Safety. 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.
doPlan: A Variable-Horizon Dataset for Multi-Stage Language-Conditioned Planning in Autonomous Driving. It centres on GitHub, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and AI Coding — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Combining Hierarchical Cognitive Process with Process Supervision for Interpretable Scene Safety Understanding. 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.
Not All Reasoning Generalizes: A Case Study on Learning Generalizable Reasoning Strategies in RLVR. It centres on Benchmarks, and also names GitHub and Meta. 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.