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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3337 stories
Noise-regularized training of quantum circuit Born machines under a finite shot budget. 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.
Prune Gradually, Adapt Sparsely: Efficient Pruning of Large Language Models at Extreme Sparsity. It centres on Inference, and also names Perplexity. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Learning Quality-Controllable Robot Policies with Iterative Hindsight Relabeling. It centres on Benchmarks, and also names Inference. Reported by arXiv. Bharat Hunt files it under Robotics and AI Regulation — the section covering embodied AI, humanoids, autonomous vehicles and drones.
Text Generation in Low-Resource Languages Using Human-Curated Vocabularies. The story centres on GitHub. 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.
Profiling a Frontier Agent with EBench: From Direct Control to Harness with Policy. It centres on Multimodal, and also names GPT and GitHub. 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.
Constrained Decoding: Harmful or Beneficial? Revisiting Its Impact on LLM Performance. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under Open Source AI and AI Models — the section covering open-weight models, permissive licences and community releases.
Interpretable sparse fine-tuning with TopKLoRA enables faithful circuit discovery. It centres on Fine-tuning, and also names Gemma and GitHub. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Dimension-free regimes for unadjusted Langevin in ridge-separable models: A subspace robust Wasserstein analysis. 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.
Predictable performance is suboptimal, and what it means for model routing. It centres on Benchmarks, and also names Fine-tuning. 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.
Automated Materials Data and Knowledge Extraction using Machine Learning and Large Language 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.
CAPSafe: A Benchmark for Contextual Action and Plan Safety Reasoning in Embodied Agents. It centres on Benchmarks, and also names Gemini. Reported by arXiv. Bharat Hunt files it under Robotics and AI Models — the section covering embodied AI, humanoids, autonomous vehicles and drones.
Game of Phones: Harnessing Game Theory and LLMs in 'Bot Wars' to Counteract Phone Scams. It centres on Fine-tuning, and also names Benchmarks and AI Safety. Reported by arXiv. Bharat Hunt files it under AI Research and AI Coding — the section covering papers, benchmarks, evaluations, interpretability and safety results.
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.