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 5 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.
292 stories
Gains and Collapse in On-Policy Distillation:A Reinforcement Learning Perspective. The story centres on GitHub. Reported by arXiv. Bharat Hunt files it under AI Regulation — the section covering law, policy, courts, standards and government positions on AI. Open the original report for the full detail.
Mem++: Non-Destructive Memory for Long-Term Organizational LLM Agents. It centres on Benchmarks, and also names GPT and RAG. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Exact Feedback Is Not Control: Evaluating Text-based Closed-Loop Revision in LLMs. 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.
When Context Misleads: In-context Learning with Jurisdiction in Large Language Models. It centres on Benchmarks, and also names Fine-tuning and GitHub. 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.
IdeaAMBIG: Benchmarking Implementation-Critical Gaps in Research-Idea Specifications. It centres on Benchmarks, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Research and AI Coding — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Retrofitting Code Using LLMs to Support Exceptional Behavior. It centres on Benchmarks, and also names GitHub and Qwen. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Models — the section covering code generation, developer agents, IDEs and software engineering.
Automated agent evaluation with Amazon Bedrock AgentCore and GitHub Actions. It centres on Benchmarks, and also names Amazon and GitHub. Reported by AWS. Bharat Hunt files it under AI Agents and AI Coding — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Dhārā Bench: An Evidence-Oriented Retrieval Benchmark for Indian Knowledge Systems. It centres on Benchmarks, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Research and AI in India, and tracks it as India coverage — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Every Token Needs Its Own Teacher: Multi-teacher Adaptive On-policy Self-distillation. The story centres on GitHub. Reported by arXiv. Bharat Hunt files it under AI Regulation and AI Research — the section covering law, policy, courts, standards and government positions on AI.
SurveyGraph: Generating Academic Surveys via Methods-Entity Knowledge Graphs. It centres on Benchmarks, and also names Qwen and GitHub. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Loopholing All the Way: Language Modeling with pure Self-Conditioning. It centres on Fine-tuning, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Funding — the section covering code generation, developer agents, IDEs and software engineering.
Co-Evolving Acting and Forecasting for Language Agents. It centres on Inference, and also names Benchmarks and GitHub. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Regulation — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
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.