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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45 stories
Perplexity trusts GPT-6 Astra with end-to-end systems. It centres on Perplexity, and also names GPT. Reported by OpenAI. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
DecisionPivot: A Diagnostic Benchmark for Decision Models in LLM Systems. It centres on Benchmarks, and also names Perplexity. 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.
Learning Functional Subspaces for Neural Network Compression. It centres on Llama, and also names Perplexity. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
On the (In)effectiveness of AMR Augmentation for Large Language Models. The story centres on Perplexity. 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.
StateLoop: Persistent State for Looped Transformers. The story centres on Perplexity. 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.
Diffusion Language Models for Perplexity-Aware Black-Box Attacks. The story centres on Perplexity. 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.
Output-aware Residual Stream Pruning for Large Language Models. It centres on Inference, and also names Perplexity. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
EnergyCal: Taming Loss Spikes in Muon-Family Optimizers for Sparse MoE Training. The story centres on Perplexity. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
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.
Representation-Space MMD for Diffusion Language Models. It centres on Perplexity, and also names Benchmarks. 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.
Distribution Matching Distillation for Continuous Diffusion Language Models. The story centres on Perplexity. 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.
WUSH-KV: KV Cache Quantization with Data-Adaptive Transforms. It centres on Inference, and also names Perplexity and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
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.