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.
5345 stories
EngramEdit: Decoupled Knowledge Updates in LLMs through Conditional Memory. It centres on DeepSeek, and also names Reasoning Models. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Long-WAM: Scaling the Context of World-Action Models. 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. Open the original report for the full detail.
Rephrase Before You Act: Characterizing and Mitigating Language Sensitivity in Vision-Language-Action Models. The story centres on GitHub. Reported by arXiv. Bharat Hunt files it under AI Models and AI Regulation — the section covering a new or updated model, its capabilities, benchmarks or availability.
RoboJEPA: Scaling Robotic Latent World Models. The story centres on 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.
SciExam for ENSO: Can AI Agents Build Climate Models? The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models and AI Agents — the section covering a new or updated model, its capabilities, benchmarks or availability.
Your Prompt Should Do More: Effects of Retrieval Instructions in Embedding Models. It centres on Benchmarks, and also names 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.
RECAST: Learning to Compute the Right Context through Adaptive Evidence Routing. It centres on RAG, and also names Fine-tuning and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Tools — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Validity Without Ground Truth: What Stated-Preference Economics Offers the Evaluation of Language Models. 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.
EmbodiedRSI: Active Continual Robot Learning Through Hypothesis-Guided Co-Evolution. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under Robotics and AI Agents — the section covering embodied AI, humanoids, autonomous vehicles and drones. Open the original report for the full detail.
Before They Can Solve: Predicting Post-Training Coding-Agent Performance from Base Models. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Models — the section covering code generation, developer agents, IDEs and software engineering.
OrBIT: Structure-Guided Embedding Compression. The story centres on GPT. Reported by arXiv. Bharat Hunt files it under AI Models and AI Coding — the section covering a new or updated model, its capabilities, benchmarks or availability. Open the original report for the full detail.
ResidualQuant: KV Cache Quantization for Looped Transformers with 2-Bit Residuals. It centres on Inference, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Coding — the section covering code generation, developer agents, IDEs and software engineering.
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.