Dynamic multimodal learning aims to learn robust representations by adaptively modeling information discrepancies across…
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LLM agents are increasingly capable of executing complex tasks and of recursively improving themselves on easy-to-verify…
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Looped language models apply the same stack of layers T times to each token, which deepens the model without adding para…
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Visual disruptions can arise while a robot is executing a task, leaving a vision-language-action (VLA) policy to respond…
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When using an LLM agent in a consequential domain, making an informed decision about whether to trust its output or inte…
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Where generalization capacity--the ability to extract context-invariant relational structures--first emerges remains a c…
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Mobile GUI agents increasingly operate on interfaces influenced by users' histories and preferences, but their reliabili…
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As agents continuously improve by generating and revising Skills, the process that discovers and refines those Skills be…
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Multimodal assistants answer questions from long-term memories that contain images.After retrieval, each retrieved image…
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Multimodal large language models have become the dominant paradigm for visual understanding, but incur substantial costs…
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Tabular foundation models (TFMs) achieve strong predictive performance by conditioning on labeled demonstrations provide…
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World models are usually judged from the inside: by prediction loss, by the return a policy earns in imagination, or by…
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AI agents are increasingly being programmed to automate knowledge work over large collections of unstructured data.Such…
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LLM agents often lack the operational knowledge to act reliably in new environments, as they must discover specific tool…
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Frontier LLM agents have been shown to be capable of solving increasingly complex tasks for which humans have measurable…
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Reinforcement learning with verifiable rewards (RLVR) turns agent experience into learning signals primarily through sca…
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LLM tool-use agents operate in dynamic environments where many actions carry operational risk.However, most safety mecha…
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In semantic query engines, predicates are evaluated by machine-learned models, and the choice of a query plan affects no…
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Developing reliable models for clinical tasks, such as Medical Question Answering (QA), is severely constrained by the l…
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Large Language Model (LLM) agents are increasingly deployed in high-stakes settings such as industrial maintenance and e…
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