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.
290 stories
Training-Free Task Vectors for LLM Behavioral Control. It centres on Reliance Jio, and also names Fine-tuning and GitHub. Reported by arXiv. Bharat Hunt files it under AI Models, and tracks it as India coverage — the section covering a new or updated model, its capabilities, benchmarks or availability.
The Audit Decides the Verdict: Instrument Effects Rival Demographic Bias in LLM Decision Audits. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Answer-Distribution Trajectories: A Stochastic-Dynamics View of LLM Reasoning. It centres on Reasoning Models, and also names Benchmarks and Inference. Reported by arXiv. Bharat Hunt files it under Open Source AI and AI Models — the section covering open-weight models, permissive licences and community releases.
It Is Not My Code Anymore. The story centres on Benchmarks. 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.
Multi-Task Learning for Sparsely-Labeled Time Series: A Case Study on Cold-Hardiness Modeling. Reported by arXiv. Bharat Hunt files it under AI Research and AI Funding — the section covering papers, benchmarks, evaluations, interpretability and safety results. Open the original report for the full detail.
Let It Go or Learn to Self-Correct: Continuous Diffusion for Constrained Discrete Tasks. It centres on Inference, and also names AI Safety. Reported by arXiv. Bharat Hunt files it under Generative AI and AI Models — the section covering text, image, audio and video generation — products and their output.
PlayTrain: An Efficient Reinforcement Learning Framework for LLM-Generated Adaptable JavaScript Games. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Hardware — the section covering code generation, developer agents, IDEs and software engineering. Open the original report for the full detail.
Evaluation of Contextual Understanding in Large Language Models. It centres on Benchmarks, and also names Perplexity. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Deposon: An Auditable, Conservation-Guaranteed, Game-Theoretically Tested Scattering Layer over LLM Reasoning Paths. It centres on Benchmarks, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Do Reasoning Representations Help Humans Evaluate LLM Outputs? It centres on Benchmarks, and also names Reasoning Models. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 2. It centres on Amazon, and also names Benchmarks and Inference. Reported by AWS. Bharat Hunt files it under AI Models and AI Regulation — the section covering a new or updated model, its capabilities, benchmarks or availability.
Transformers as In-Context Samplers: From Closed-Form Diffusion to Estimation-Free Sampling. The story centres on Inference. Reported by arXiv. Bharat Hunt files it under Generative AI and AI Research — the section covering text, image, audio and video generation — products and their output.
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.