{"items": [{"seq": 1, "id": "e05551817b225bef5e8ca8d6", "url": "https://huggingface.co/blog/allenai/impactful-scheduling", "title": "Impactful scheduling for GPU clusters", "description": "", "published_at": 1791559229, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 2, "id": "ffd2818196374b7e8d985c5b", "url": "https://huggingface.co/blog/building-with-ml-intern", "title": "The model that didn't exist, so you made it yourself", "description": "", "published_at": 1791417600, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 3, "id": "88e871d5a8d26738db20168d", "url": "https://huggingface.co/blog/LiquidAI/open-d1", "title": "Multimodal open d1 decision models for the edge", "description": "", "published_at": 1791392073, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 4, "id": "16b7810afb00bdc03cf91abd", "url": "https://huggingface.co/blog/tiiuae/falcon-asr", "title": "Introducing Falcon ASR", "description": "", "published_at": 1791379263, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 5, "id": "67f5f61696a2949df2730f40", "url": "https://huggingface.co/blog/nvidia/nemotron-ioi-and-imo-2026", "title": "One Model Family, Two Gold-Level Results: Fine-Tuning Nemotron for IOI and IMO", "description": "", "published_at": 1791377131, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 6, "id": "bd1136d0fcfd6f1357de280a", "url": "https://huggingface.co/blog/microsoft/thinkingbox", "title": "The Agent Said It Was Done. The Database Disagreed.", "description": "", "published_at": 1791068208, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 7, "id": "56c490db040147f1def4aa82", "url": "https://huggingface.co/blog/ServiceNow-AI/autosynthdata", "title": "AutoSynthData: Generating Training Data for Enterprise Agents", "description": "", "published_at": 1790913691, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 8, "id": "74c2ff7e2707d1f61043b51a", "url": "https://huggingface.co/blog/open-tts-leaderboard", "title": "Open TTS Leaderboard: Scalable Evaluation for Multilingual Text-to-Speech and Voice Cloning", "description": "", "published_at": 1790726400, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 9, "id": "afa8c33f8eb7996a39419dea", "url": "https://huggingface.co/blog/MultiverseComputingCAI/getting-the-source-right-not-just-the-fact-source", "title": "Getting the Source Right, Not Just the Fact: Source-Aware Verification for MCP Agents", "description": "", "published_at": 1790687220, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 10, "id": "09d1d26fa19dd694ec40f7bb", "url": "https://huggingface.co/blog/Hcompany/holo4", "title": "Holo4: powering generalist computer-use agents", "description": "", "published_at": 1790588645, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 11, "id": "eb916b5190e379580afd8a2b", "url": "https://huggingface.co/blog/rl-environments", "title": "Welcome RL Environments to the hub", "description": "", "published_at": 1790553600, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 12, "id": "e9f63aa1f7aaa02f4024a141", "url": "https://huggingface.co/blog/evaleval-aisi", "title": "How UK AISI and EvalEval Are Making Benchmark Results Reproducible", "description": "", "published_at": 1790035200, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 13, "id": "689d78c6e007ab8e2c4f1996", "url": "https://huggingface.co/blog/transformers-llama-cpp-quants", "title": "Transformers now runs llama.cpp quants", "description": "", "published_at": 1790035200, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 14, "id": "6b3083011aeb49b1cc1d670c", "url": "https://huggingface.co/blog/omlx", "title": "Jun Kim, oMLX creator and maintainer, joins Hugging Face to support the MLX community", "description": "", "published_at": 1790035200, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 15, "id": "693b3130e25cc8808f585a69", "url": "https://huggingface.co/blog/tokenizers-v1", "title": "tokenizers v1: encode, decode and scaling, measured", "description": "", "published_at": 1789948800, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 16, "id": "a1d018f16fad79f97456f75b", "url": "https://huggingface.co/blog/ibm-research/altk-evolve-consistency", "title": "Your Agent Aced the Task. Will It Do It Again?", "description": "", "published_at": 1789488044, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 17, "id": "85052f9befba2c4e17fa41a5", "url": "https://huggingface.co/blog/asyncgrpo-lora-hfjobs", "title": "Async GRPO with LoRA across HF Jobs: a bucket, a proxy, and no NCCL", "description": "", "published_at": 1788998400, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 18, "id": "075fed980e67c694db46ceda", "url": "https://huggingface.co/blog/gradio-workflow-1111", "title": "Rebuilding AUTOMATIC1111 with Gradio Workflow", "description": "", "published_at": 1788998400, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 19, "id": "fffbcba03b0b217e48932bf1", "url": "https://huggingface.co/blog/Hcompany/neomme", "title": "NeoMME: an efficient Multimodal-native and Multilingual Encoder", "description": "", "published_at": 1788441228, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 20, "id": "a139f80b159295ada71d0ef0", "url": "https://huggingface.co/blog/grpo-with-trl-ifstruct", "title": "Fine-tuning a 350M Model for Better Structured Outputs in 100 GRPO Steps", "description": "", "published_at": 1788393600, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 21, "id": "cdd1118267ee925c63286ac8", "url": "https://huggingface.co/blog/funes", "title": "Give Your Coding Agents a Memory You Own", "description": "", "published_at": 1788393600, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 22, "id": "b5500bc6503561c622e234c7", "url": "https://huggingface.co/blog/train-to-paint-with-code", "title": "Training a coding model to paint watercolours with TRL and OpenEnv", "description": "", "published_at": 1788393600, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 23, "id": "ad90e6779ea3045b3b9ff330", "url": "https://huggingface.co/blog/allenai/benchmirt", "title": "BenchMIRT: What are LLM benchmarks actually measuring?", "description": "", "published_at": 1788298747, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 24, "id": "91dad0068ec24e5bcea7adc0", "url": "https://huggingface.co/blog/webgpu-kernels", "title": "Introducing @huggingface/kernels: 200+ WebGPU Kernels for Local AI", "description": "", "published_at": 1788220800, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 25, "id": "4d3b17a749f42c957e926aa5", "url": "https://huggingface.co/blog/open-asr-leaderboard-global-south", "title": "The Open ASR Leaderboard Adds Its First Global South Language", "description": "", "published_at": 1787875200, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 26, "id": "17177c100c9150295f9a783a", "url": "https://huggingface.co/blog/train-multi-vector-encoder", "title": "Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers", "description": "", "published_at": 1787702400, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 27, "id": "d21068479952e40383665c65", "url": "https://huggingface.co/blog/ibm-granite/granite-4-2", "title": "Granite 4.2 LLMs: How They're Built", "description": "", "published_at": 1787670854, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 28, "id": "f1c76f23a788b6884a2877cd", "url": "https://huggingface.co/blog/MultiverseComputingCAI/quantization-aware-healing", "title": "Quantization-Aware Healing: a compressed, 4-bit model that outperforms its full-precision original", "description": "", "published_at": 1787657964, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 29, "id": "9b54a38fa1b1a3f1fc1fd60d", "url": "https://huggingface.co/blog/gradio-workflow-guide", "title": "Wire It, Run It, Deploy It: AI Workflows in Gradio", "description": "", "published_at": 1787616000, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}, {"seq": 30, "id": "966123ef613d7e9a038f2daf", "url": "https://huggingface.co/blog/pwc-search", "title": "How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code", "description": "", "published_at": 1787270400, "first_seen_at": 1791705646, "sources": [{"id": "huggingface", "name": "Hugging Face", "category": "tools", "language": "en"}]}], "has_more": true, "next_cursor": 30, "next_offset": null, "resume_url": "/v1/public/news?after=30", "latest_cursor": 2184, "collected_at": 1791705648, "generated_at": 1791722026, "stale": false, "refresh_mode": "operator-collected snapshot; no automatic refresh yet", "read_only": true, "untrusted_content": true, "unknown_params": [], "note": "Descriptions are publisher excerpts. Claims are not verified. Duplicate URLs merge; different reports of the same story do not. Cursors detect newly inserted URLs, not edits."}