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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322 stories
Beyond Selected Breakthroughs: Evaluating Language Models on Randomly Sampled Mathematical Conjectures. The story centres on GPT. 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.
Training Reasoning Models to Generate Diverse Scientific Ideas. It centres on Reasoning Models, and also names Claude and GPT. 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.
When Victorian Becomes a Prompt: Literary Periodization as a Generative Constraint in 100 AI-Generated Novels. It centres on GPT, and also names Qwen and Llama. Reported by arXiv. Bharat Hunt files it under AI Models and Generative AI — the section covering a new or updated model, its capabilities, benchmarks or availability.
Profiling a Frontier Agent with EBench: From Direct Control to Harness with Policy. It centres on Multimodal, and also names GPT and GitHub. Reported by arXiv. Bharat Hunt files it under AI Models and Robotics — the section covering a new or updated model, its capabilities, benchmarks or availability.
Green Code or Costly Code? Evaluating the Energy Costs of Iterative LLM-Based Code Optimizations. It centres on Benchmarks, and also names Inference and GPT. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Models — the section covering code generation, developer agents, IDEs and software engineering.
Recognizing Study Lineage Is Not Enough: Over-Crediting Same-Trial Evidence in LLM-Based Medical Verification. The story centres on GPT. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
MuninAI: A Self-Hosted Agentic Framework for Independent Research Groups. It centres on Benchmarks, and also names Qwen and GPT. Reported by arXiv. Bharat Hunt files it under AI Research and Open Source AI — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Looking Complete Is Not Being Grounded: Evaluating LLM Sitreps Against Human-Authored Situation Reports. It centres on Benchmarks, and also names Google and Gemini. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
WorldSolver: Can LLM Agents Simulate the Physical Dynamics via Solver Generation? It centres on Benchmarks, and also names GPT and Claude. Reported by arXiv. Bharat Hunt files it under AI Coding and Robotics — the section covering code generation, developer agents, IDEs and software engineering.
Same Claim, Different Interpretations: How LLM Agents Resolve Ambiguity in Scientific Claims. It centres on Benchmarks, and also names GPT. 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.
CLIFT: Conformal Self-Verification for Web Agent Training and Test-Time Scaling. It centres on GPT, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under Open Source AI and Enterprise AI — the section covering open-weight models, permissive licences and community releases.
ChatGPT maker wants to be the App Store for AI as safety concerns grow. It centres on GPT, and also names OpenAI and AI Safety. Reported by The Economic Times. Bharat Hunt files it under AI Tools and AI Research — the section covering applications people use — assistants, editors, search, productivity.
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.