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
Tracing and Taming Hallucinated Terms via Subsequence-Association Filtering and Breadth-Aware Selection for LLM Query Expansion. The story centres on AI Safety. Reported by arXiv. Bharat Hunt files it under AI Research — 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.
QuSema: Detecting Silent Bugs in Quantum Libraries via Quantum-knowledge-enhanced Agents. It centres on Benchmarks, and also names Claude Code and DeepSeek. 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.
JEV versus LLMs: Accuracy, Cost and Calibration on Seven Political Science Replications. It centres on GPT, and also names OpenAI. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Why Alzheimer's Speech Screening Fails to Generalize: Bridging the Deployment Gap via Cross-Corpus Evidence Anchoring. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under Enterprise AI and AI Research — the section covering deployment inside businesses — platforms, adoption, cost, integration.
MILO: Efficient Many-shot In-Context Learning with Block-wise Low-rank Compression. It centres on Inference, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Hardware and Enterprise AI — the section covering chips, accelerators, data centres, on-device inference and supply.
Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms. It centres on Fine-tuning, 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.
PP-Net: A Hybrid Physical-Prior Neural Network for Scattered Light Removal in Biomedical Images on Embedded Devices. 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.
Where Does Alignment Emerge and What Does It Mean? A Closer Look at the Platonic Representation Hypothesis. It centres on AI Safety, and also names Multimodal 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.
2D Gum-Net: Unsupervised Dense Elastic Image Registration via Symmetric Correlation and Spectral Pooling. It centres on AI Safety, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Hardware and AI Research — the section covering chips, accelerators, data centres, on-device inference and supply.
CRESiST: Self-Enhancing Explorative Policy Learning for Simultaneous Speech Translation. It centres on Inference, and also names Benchmarks and AI Safety. 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.
Evaluating LLMs as Judges of Counterspeech Quality Against Online Hate Speech. It centres on Reasoning Models, and also names Qwen and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
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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.