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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Greedy Decoding Is Not Precision-Invariant: Cross-Precision Output Divergence in LLM Inference. It centres on Inference, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Informed Masking: Structure-Aware Perturbation for Reinforcement Learning in Diffusion Large Language Models. It centres on Inference, 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.
Cola2: Co-Adaptive Hierarchical Language Modeling with Continuous Semantic Compression and Balanced Discrete Generation. It centres on Inference, and also names Llama. Reported by arXiv. Bharat Hunt files it under Generative AI — the section covering text, image, audio and video generation — products and their output.
GoiBERT: Compact Vietnamese Language Models via Two-Stage Knowledge Distillation. It centres on Benchmarks, and also names Inference and GitHub. Reported by arXiv. Bharat Hunt files it under AI Models and Computer Vision — the section covering a new or updated model, its capabilities, benchmarks or availability.
FuTransformer: FP8 prefill and INT4 decode for Llama-style inference on Hopper. It centres on Llama, and also names Inference and NVIDIA. Reported by arXiv. Bharat Hunt files it under AI Models and AI Hardware — the section covering a new or updated model, its capabilities, benchmarks or availability.
Humanize Olympiad Agents: A Multi-Session Workflow for Olympiad Problem Solving with Solve, Review, Wiki, Verify. It centres on Inference, and also names GPT. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
A Living Benchmark for Information Retrieval from Electronic Health Records. It centres on Benchmarks, and also names Inference. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
EnterpriseVal: Quantifying the Efficacy, Reliability and Value of Generative AI in the Enterprise. It centres on Benchmarks, and also names Inference. Reported by arXiv. Bharat Hunt files it under Enterprise AI and Generative AI — the section covering deployment inside businesses — platforms, adoption, cost, integration.
MIRAGE: Multi-Perspective Creative Language Model Reasoning with Reinforcement Learning Guidance. It centres on Inference, and also names Benchmarks and Reasoning Models. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Welcome Muse Spark Open: open-weight frontier multimodal mixture-of-experts model from Meta. The story centres on Meta. 3 sources have covered it so far, including The Economic Times, AWS and Hugging Face. Bharat Hunt files it under Open Source AI and AI Models — the section covering open-weight models, permissive licences and community releases.
On the Tip of the Tongue: First-Token Cueing as a Behavioral Probe of Recall Failures in LLMs. It centres on Benchmarks, and also names Inference. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Input-Blind Controls Produce Substantial Oracle Headroom for Layer Programs in Multiple-Choice Evaluation. It centres on Benchmarks, and also names Inference and Llama. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
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.