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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146 stories
Revision-Based Learning from Interactive Experience and Feedback. The story centres on Fine-tuning. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Models — the section covering code generation, developer agents, IDEs and software engineering. Open the original report for the full detail.
Too much code, too little shipped: Why AI needs a software factory. Reported by YourStory. Bharat Hunt files it under AI Coding and AI Agents, and tracks it as India coverage — the section covering code generation, developer agents, IDEs and software engineering.
GPUPhysBench: Benchmarking Coding Agents for Correct and Efficient GPU Physics Simulation. It centres on Benchmarks, and also names NVIDIA. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Hardware — the section covering code generation, developer agents, IDEs and software engineering.
Beyond Attack Success Rate: Cost-Aware Metric for Evaluating Iterative LLM Jailbreaks. It centres on Benchmarks, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Models — the section covering code generation, developer agents, IDEs and software engineering.
ScienceClaw: Benchmarking Continual Self-Evolution of AI-for-Science Agents Across the Natural and Social Sciences. It centres on Benchmarks, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Coding — the section covering code generation, developer agents, IDEs and software engineering.
ParanoiaEval: Benchmarking Unnecessary Defensive Work in Agentic Coding. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Agents — the section covering code generation, developer agents, IDEs and software engineering.
A Case Study in Assuring AI-Written Software. The story centres on Meta. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Research — the section covering code generation, developer agents, IDEs and software engineering. Open the original report for the full detail.
LoGRA: Scaling LLM Reinforcement Learning with Low-Rank Gradient Sketches. The story centres on GitHub. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Hardware — the section covering code generation, developer agents, IDEs and software engineering.
From Abstraction to Action: DSLs for Natural Language Abstraction Interpretation and Execution. It centres on Inference, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Coding — the section covering code generation, developer agents, IDEs and software engineering.
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.
AECP: Artifact-Exclusive Communication Protocol for Multi-Agent Code Generation. The story centres on DeepSeek. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Agents — the section covering code generation, developer agents, IDEs and software engineering.
When Requirements Interact: Scaling Long-Horizon Coding via Interdependent Specifications. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Models — the section covering code generation, developer agents, IDEs and software engineering.
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.