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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4800 stories
Word-Level Text Unmixing via Evidence-Preserving Ownership Routing with Language Models. It centres on Inference, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Learning Beyond What You Sample: Off-Policy-Aware Cross-Model Trajectory Exchange for RLVR. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Regulation and AI Models — the section covering law, policy, courts, standards and government positions on AI.
It's Not What the Image Shows: Irrelevant Context Destabilises VLM Judges Without Informing Them. 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.
Beyond Token Scale: Chunk-Level Sparse Autoencoders for Reliable Semantic Feature Discovery. Reported by arXiv. Bharat Hunt files it under AI Tools and AI Research — the section covering applications people use — assistants, editors, search, productivity. Open the original report for the full detail.
JEV-as-a-Judge: Accept When Confident, Escalate When Unsure. It centres on Benchmarks, 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.
Topology-Stratified Materials Discovery with A Flow-Based Generative Model. It centres on Benchmarks, and also names Fine-tuning. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Pretraining Data Scale Reverses the Muon-AdamW Fine-Tuning Gap. 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.
DeliverBench: Benchmarking AI Agents on Delivering Realistic Multi-Stage Professional Projects. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Agents — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Reward Misspecification Degrades Chain-of-Thought Monitorability. It centres on Reasoning Models, and also names AI Safety 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.
Adaptive Replay Refinement: Allocating Test-Time Compute Between Revision and Resampling. It centres on Inference, and also names Benchmarks and GitHub. Reported by arXiv. Bharat Hunt files it under AI Funding — the section covering rounds, valuations, acquisitions and investor moves in AI.
RouterWorld: Scaling Conversational AI with Latency-Aware LLM Routing. 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.
SimForcing: Distilling Simulation Motion Priors into Real-Domain Robot World Models. It centres on Inference, and also names Benchmarks and GitHub. 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
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.