Meta FAIR's AI Research Preference Models rank unexecuted ML candidates, raising AIRS-Bench from 0.684 to 0.729 without ...

Google releases TimesFM-3, a 330M parameter zero-shot foundation model for multivariate time series forecasting in one ...

Benchmarking the lowest-latency inference APIs for voice agents: measured TTFT, time to first audio, and full-pipeline ...

Keenable AI open-sources NEEDLE, a live benchmark that rebuilds search queries hourly and scores 15 APIs for agents.

Google introduces EnvHarness, a programmable layer that reshapes static LLM agent environments without modifying their code.

Princeton, Ant Group and Stanford built AQuA, two self-improving quant research agents whose sealed sandbox makes data leakage unwritable ...

LandingAI has shipped Agentic Document Extraction Gen2, a rebuild of its document stack on the DPT-3 model family. Chunks are retired in favor of a document, page and block tree. DPT-3 Pro grounds to ...

Google has open-sourced Mantis, a stack-agnostic toolkit of security review skills for AI coding agents. It runs the full vulnerability lifecycle: sweep the code, filter false positives, reproduce the ...

Most visual document retrievers in production today are hand-me-downs. ColPali and the models that followed it take a generative vision-language model and repurpose it as an encoder. The result still ...

AI weather models have spent three years closing the gap with physics-based forecasting, but two problems stayed open: resolution too coarse for local terrain, and initialization tied to numerical ...

Multi-agent workflows have changed the shape of local inference. A lead agent decomposes a task and spawns subagents. What looked like one user request becomes dozens of independent model calls.

This week, Meta Superintelligence Labs released Muse Spark 1.3. It is the fourth Muse Spark release in five months, and the target is long-horizon agentic and coding work rather than single-turn ...