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 ...

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

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

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 ...

Google Research has released ToolGrad, an ACL 2026 Findings framework that inverts tool-use dataset generation: it builds a verified API chain first, then writes the matching user query. Guided by ...

Production LLM applications rarely receive a question nobody has asked before. Support assistants and RAG pipelines field the same intents thousands of times a ...

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 ...

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.

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 ...

The hard part of running an open-weights model locally was never the model. It was everything before it, reading VRAM specs, guessing which quantization fits, setting context length and GPU layer ...