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.
Updated 1 hour ago142 stories in the last 24 hours
3432 stories
HydraLLM: Adaptive Width Slicing for Elastic Text and Vision-Language Models. It centres on Data Centers, and also names Multimodal and Inference. 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.
Beyond Outcome Rewards: Constructing and Assigning Retrieval Credit for Search Agents. It centres on Reliance Jio, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research, and tracks it as India coverage — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Requirement-Bound Verified Commissioning: A Frozen Four-Billion-Parameter Local Model as a Candidate Generator under an External Acceptance Layer with Verification and Release Authority. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models and AI Funding — the section covering a new or updated model, its capabilities, benchmarks or availability.
Flash-dLLM: IO-Aware KV Caching and Parallel Decoding for Fast, Memory-Efficient Diffusion LLMs. It centres on Inference, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under Generative AI and AI Hardware — the section covering text, image, audio and video generation — products and their output.
Assessing the Impact of Retrieval-Augmented Generation on Algorithmic Problem-Solving. It centres on RAG, and also names Benchmarks and Inference. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Research — the section covering code generation, developer agents, IDEs and software engineering.
A Low-Rank Space Captures Linear Alignment Between LLM and Human Neural Activity During Naturalistic Language Listening. It centres on AI Safety, 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.
Decision and System One models in rheumatology: accuracy and calibration on specialty-training examination questions and diagnostic case vignettes. It centres on Benchmarks, and also names Microsoft and GPT. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
From Self-Confidence to Statistical Accuracy: Scaling Human-in-the-Loop Evaluation with Direct and LLM-Assisted Auditing. It centres on Benchmarks, and also names Multimodal and Inference. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Can LLM Annotators Match Human Consistency? Benchmarking Human Agreement and Optimizing Multi-Agent with Contrastive Knowledge. It centres on Benchmarks, and also names AI Safety and GitHub. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Research — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
How Ground Truth Shapes Retrieval Scores: Evidence-Aware Evaluation of a Retrieval-Augmented Generation System for Breast Lesions. It centres on Benchmarks, and also names RAG and DeepSeek. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
From Triage to Impact: A Multi-Hop Reasoning Benchmark for Explainable Persian Hate Speech. It centres on Benchmarks, and also names Inference and GitHub. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Target leakage, not model class, explains reported accuracy in survey-based cardiovascular screening: a leakage-tiered audit of glass-box and tabular foundation models. It centres on Inference, and also names Nothing and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models and Enterprise AI — 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
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.