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 22 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.
HTN-Orchestrate: A Hierarchical Task Network Framework for Multi-Agent Orchestration. It centres on Benchmarks, and also names DeepSeek. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Models — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Structure-Aware Skill Retrieval and Arbitration for Optimization Modeling. It centres on DeepSeek, 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.
Rare, Relevant, and Still Wrong: How Memory Fails LLM Group Decisions. It centres on Benchmarks, and also names Llama and DeepSeek. 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.
Advancing Clinical Genomic Analysis with a Skill-Centred Agent. It centres on Benchmarks, and also names DeepSeek. 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.
SelfSearch: Reward-Free Search for Self-Improving Agents. It centres on Benchmarks, and also names DeepSeek. Reported by arXiv. Bharat Hunt files it under AI Tools and AI Research — the section covering applications people use — assistants, editors, search, productivity.
Adaptive DHiSparse: Speculative Decoding over a Load-Adaptive KV Hierarchy. The story centres on DeepSeek. 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.
CRISP: Co-designing Pruning and Scheduling for Efficient MoE Inference on Edge Servers. It centres on Inference, and also names Mistral and DeepSeek. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
MWE-ECL: Recoverable Long-Range Context Does Not Always Override Local Lexical Priors. The story centres on DeepSeek. 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.
DeepSeek, Moonshot used OpenAI's GPT-6 Astra to train latest models: report. It centres on DeepSeek, and also names Moonshot AI and OpenAI. The Economic Times and The Indian Express have both covered it. Bharat Hunt files it under AI Models and AI Coding — the section covering a new or updated model, its capabilities, benchmarks or availability.
FeatLens: Feature-Guided Dynamic Code Graph Construction and Retrieval for Repository-Level Code Generation. It centres on DeepSeek, and also names GPT. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Research — the section covering code generation, developer agents, IDEs and software engineering.
Linear Probes Transfer from Base to Distilled Language Models despite Rotation. It centres on Llama, and also names DeepSeek and Reasoning Models. 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.
PresenceBench: An Exploratory Evaluation of Large Language Model Adaptation to User State. It centres on Benchmarks, and also names Claude and DeepSeek. 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.
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
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.