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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SciWalker: Synthesizing Scientific Coding Problems with Operator Graphs and Execution Feedback. 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.
Not All Reasoning Generalizes: A Case Study on Learning Generalizable Reasoning Strategies in RLVR. It centres on Benchmarks, and also names GitHub and Meta. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Ontology-Guided Knowledge Graph Construction from Structured Metadata and Climate Science Publications. It centres on Gemini, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Research and AI Agents — the section covering papers, benchmarks, evaluations, interpretability and safety results.
When LLMs Forget What They Believe: Characterizing State Integrity Collapse in Long-Horizon Dialogues. It centres on Benchmarks, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Image Classifiers are Efficient Self-Supervised Video Representation Learners. 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. Open the original report for the full detail.
Learning Skills from Historical Action Trajectories: Action Experience Dictionary for World Action Models. It centres on Reliance Jio, and also names Benchmarks 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.
G$^2$PTQ: Improving LLM Post-Training Quantization with Generalized Gradient Compensation. It centres on AI Safety, and also names 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.
EquivSVA: A Formally Verified Dataset of Behavioral Assertions Across Equivalent RTL Implementations. It centres on Benchmarks, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results.
CoopUQ: Robust Multi-Robot Social Navigation via Uncertainty-Aware Cooperative Forecasting. The story centres on GitHub. Reported by arXiv. Bharat Hunt files it under Robotics and AI Agents — the section covering embodied AI, humanoids, autonomous vehicles and drones. Open the original report for the full detail.
BrainNet Studio: A Unified Toolkit for Brain Network Construction, Intelligent Analysis, and Visualization. The story centres on GitHub. Reported by arXiv. Bharat Hunt files it under AI Tools and AI Models — the section covering applications people use — assistants, editors, search, productivity.
CoDe-LoRA: Mitigating the Orthogonality Dilemma in Continual Learning of LLMs via Knowledge Consolidation and Decoupling. 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.
Mutable Transcripts: Mitigating Context Pollution through Editable Conversation State. The story centres on GitHub. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results. Open the original report for the full detail.
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.