AI-Driven Reproducibility and Analytical Robustness in Scientific Discovery
Reproducible and analytically robust research findings are essential to scientific progress, but evaluating these pro...
每天自动聚合 AI 领域最新动态
Reproducible and analytically robust research findings are essential to scientific progress, but evaluating these pro...
Fine-tuning large language models (LLMs) can induce behaviors beyond those explicitly targeted. For example, training...
Pixel-space diffusion models have recently re-emerged as a compelling alternative to latent diffusion, avoiding the l...
Peer review is under strain from the growth of submissions, and review comments written by humans or AI can misstate ...
Retrieval is a fundamental task in multimodal systems: given an image or text query, the goal is to find the most rel...
World Action Models (WAMs) commonly couple video and action experts through dense, layer-wise Mixture-of-Transformers...
Progress toward general intelligence in the physical world requires scaling robot learning across diverse environment...
Repository-level software engineering (SWE) is a challenging long-horizon setting: agents must reason over extended i...
Large language model (LLM) agents can keep scientific experiments running for months with little human supervision, b...
AI agents increasingly use files and software tools to produce professional deliverables. Such work draws on material...
Reliable deployment of LLM-based multi-agent systems calls for runtime auditors that predict terminal outcomes from o...
We study how vision-language models (VLMs) can learn to think and actively explore in 3D space. Instead of providing ...