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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4967 stories
PhysiCalWorld: In-Context Physics Calibration for World Models. It centres on Fine-tuning, and also names Inference. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Environment Duels: A Microcosm of LLM Co-Evolution. 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.
The End of Consensus Research? 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.
Quant-Arena: Benchmarking LLM Agents for Quantitative Trading Research. It centres on Benchmarks, and also names GPT. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Multimodal Embodied Agents: A Unified Capability-centric Perspective from Computer-Use to Robot-Use. It centres on Multimodal, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under Robotics and AI Agents — the section covering embodied AI, humanoids, autonomous vehicles and drones.
Asymmetric On-Policy Distillation Learns In-Context Exploration. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Regulation — the section covering law, policy, courts, standards and government positions on AI. Open the original report for the full detail.
BatchBench: Benchmarking AI Robustness to Batch Effects and Domain Shift in Biomedical Images. 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.
Did the Problem Actually Get Harder? Testing LLMs on Paired P and NP-Complete Problems Hardened by Adversarial Multi-Agent Rewriting. The story centres on Benchmarks. 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.
Differentially Private Sparse Reward Estimation with Preference Feedback. It centres on Reliance Jio, and also names AI Safety and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models, and tracks it as India coverage — the section covering papers, benchmarks, evaluations, interpretability and safety results.
AtomicRL: Atomic Reinforcement Learning for Long-Horizon Robotic Manipulation. Reported by arXiv. Bharat Hunt files it under AI Regulation — the section covering law, policy, courts, standards and government positions on AI. Open the original report for the full detail.
GBClaw: An agentic AI framework for atomistic grain boundary research and mechanistic discovery. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Research — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
UniWALM: Unified World Action Language Model for Embodied Robot Control. It centres on Inference, and also names Reasoning Models. Reported by arXiv. Bharat Hunt files it under Robotics and AI Models — the section covering embodied AI, humanoids, autonomous vehicles and drones.
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
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.