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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716 stories
From Structured Records to Patient Narratives: Preserving Clinical Alignment in LLM-Generated Health Summaries. It centres on AI Safety, and also names RAG and Inference. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Librarian Agents: Training LLMs to Curate Long-Context Workspaces that Anticipate Future Queries. It centres on Inference, and also names Claude Code. 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.
HydraLLM: Adaptive Width Slicing for Elastic Text and Vision-Language Models. It centres on Data Centers, and also names Multimodal and Inference. Reported by arXiv. Bharat Hunt files it under AI Models and AI Hardware — the section covering a new or updated model, its capabilities, benchmarks or availability.
Flash-dLLM: IO-Aware KV Caching and Parallel Decoding for Fast, Memory-Efficient Diffusion LLMs. It centres on Inference, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under Generative AI and AI Hardware — the section covering text, image, audio and video generation — products and their output.
From Self-Confidence to Statistical Accuracy: Scaling Human-in-the-Loop Evaluation with Direct and LLM-Assisted Auditing. It centres on Benchmarks, and also names Multimodal and Inference. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
From Triage to Impact: A Multi-Hop Reasoning Benchmark for Explainable Persian Hate Speech. It centres on Benchmarks, and also names Inference and GitHub. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Watermarkable Multi-Draft Speculative Sampling via Poisson Processes. The story centres on Inference. Reported by arXiv. Bharat Hunt files it under Enterprise AI — the section covering deployment inside businesses — platforms, adoption, cost, integration. Open the original report for the full detail.
Target leakage, not model class, explains reported accuracy in survey-based cardiovascular screening: a leakage-tiered audit of glass-box and tabular foundation models. It centres on Inference, and also names Nothing and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models and Enterprise AI — the section covering a new or updated model, its capabilities, benchmarks or availability.
$Φ$asmaNet: A Staged Spectral Token-Refinement Architecture for Fast Gravitational-Wave Signal-to-Noise Ratio Prediction. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Hardware — the section covering chips, accelerators, data centres, on-device inference and supply.
Not All Dimensions Are Equal: Outlier-Aware Attention Linearization with Grouped Quadratic Kernels. It centres on Inference, and also names Benchmarks and 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.
DeepEdu-v1: Efficient and Scalable Agentic LLMs for Vietnamese Education. It centres on GPT, and also names Inference and Fine-tuning. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Hardware, and tracks it as India coverage — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
NgramRL: Accelerating RL Post-Training for Structured Generation via Rollout-Aware N-gram Speculative Decoding. Reported by arXiv. Bharat Hunt files it under AI Hardware and AI Models — the section covering chips, accelerators, data centres, on-device inference and supply. Open the original report for the full detail.
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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.