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 10 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.
387 stories
Towards Enriching Design-Time Models with Evidence from Simulation and Operational Activities. Reported by arXiv. Bharat Hunt files it under AI Models and Robotics — the section covering a new or updated model, its capabilities, benchmarks or availability. Open the original report for the full detail.
Hierarchical Continuous Diffusion Language Models. It centres on Nothing, and also names Perplexity and GitHub. Reported by arXiv. Bharat Hunt files it under Generative AI and AI Models — the section covering text, image, audio and video generation — products and their output.
A2M: Trace-Optimized Agent Hijacking in the MCP Ecosystem. It centres on Model Context Protocol, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Coding — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-of-Thought in Frontier Models. It centres on Reasoning Models, and also names GPT and Benchmarks. 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.
Evaluating and Improving Evidence-Grounded Fact-Checking in LLMs via Multi-Round Evidence Ablation. 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.
Rethinking Neural Thickets Without Weight Perturbations. The story centres on Inference. 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.
Scaling Multilingual Safety and Reasoning Evaluation through Reasoning-Guided Translation. The story centres on 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.
DoubtLess: Training-Free Contrastive Decoding for Efficient Reasoning. It centres on Reasoning Models, and also names Benchmarks and Inference. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Models — the section covering code generation, developer agents, IDEs and software engineering.
Rubrics from the Task, Verdicts from Evidence: Pointwise Rubric Rewards with Tool-Augmented Judges. Reported by arXiv. Bharat Hunt files it under AI Tools and AI Regulation — the section covering applications people use — assistants, editors, search, productivity.
OVAL: Output-Aware Local Page Bases for KV Cache Retrieval. It centres on Inference, and also names Benchmarks and GitHub. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
GRASP: Generating, Revising, and Assessing for Strategic Planning with Agentic AI. It centres on Reasoning Models, and also names GPT. Reported by arXiv. Bharat Hunt files it under AI Agents — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
CRoS: Causality Reward on Scrambled CoTs Improves Accuracy and Reasoning Faithfulness. The story centres on Gemma. Reported by arXiv. Bharat Hunt files it under AI Models — 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
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.