Bob M

C²-Cite raised citation quality by an average of 5.8% and response correctness by 17.4% on the ALCE benchmark. And the gap between those two numbers is the story. LLM citation and source tracking is the discipline of proving that every claim in a model's output

Graph-of-Agents landed at ICML 2025 with a blunt message for anyone shipping LLM agent pipelines: procedural graph architectures beat hand-wired chains. The framework treats each agent as a node and each communication channel as a directed edge, then constructs that graph fresh for every query instead of following a flowchart

Somewhere past 130,000 GitHub stars, Ollama stopped being a curiosity and became the front door everyone walks through. Underneath it sits a local LLM toolchain where every layer ships under a permissive license. Inference, serving, web UIs, vector stores. So the short answer to whether open-source LLM toolchains can

Open-source multimodal LLMs stopped pretending video is just a pile of images with a transcript stapled on. Qwen3-Omni is the proof: a 30B-A3B open-weight checkpoint, mixture-of-experts, that takes text, image, audio. And video in and gives you text plus realtime speech out the other side. Its own team calls it

Qwen 4 now ships a native 1M-token context window under an Apache 2.0 license. And the open source long context LLM field around it filled in fast: DeepSeek V4 Pro at 1M-class, Gemma 4.5 at 1M, Mistral Voyage Pro at 512K. That's your shortlist if you&

WearableQA put 14 big language models through 4,084 health questions built from real wearable data. And most of them finished below 60% accuracy (papers.cool). WearableQA is a new benchmark for health reasoning over real-world wearable data, listed under Computation and Language on arXiv. Every question carries 10 answer