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This paper asks a direct question: can current AI agents carry out open-ended AI research on their own? The authors introduce a method calle
Researchers introduce OmniQEC, an artificial intelligence system that searches for quantum error‑correcting codes that work well on real qua
This paper introduces ClinFusion, a multimodal large language model (MLLM) designed to understand medical images the way clinicians do. The
This paper introduces VLM-IE3D, a way to give vision-language models a stronger sense of 3D space using only ordinary RGB video. The authors
This paper argues that large language models (LLMs) and agentic AI should not be allowed to invent numerical answers for power systems. The
Researchers introduce GigaPath-Flash and GigaTIME-Flash, two compact foundation models for pathology that aim to make whole-slide image anal
This paper shows that text placed by outsiders on public websites can sometimes end up in the data used to train large language models (LMs)
This paper studies a common blind spot in automated coding agents: they often do far more reading and checking than a task truly needs. The
This paper reviews what researchers know so far about metacognition in large language models (LLMs). Metacognition means the ability to moni
This paper proposes a structured way to study how so-called coding agents — large language models (LLMs) that write and run code — behave wh