Zero-shot coordination in embodied settings requires acting while the partner is intermittently out of view, leaving exi…
Legal intelligence aims to support reliable decision-making across long-horizon legal processes involving evolving case…
Product Identification has sprung up to become one of the most challenging problems in the automation of the retail indu…
End-to-end planners based on waypoint regression achieve strong open-loop accuracy, but they primarily learn to mimic ex…
Attacker ASV systems for voice anonymization have been studied primarily in English, leaving their behavior in multiling…
Multimodal large language models (MLLMs) advance rapidly, while conventional benchmark development lags behind, delaying…
Conversational MLLM agents are increasingly expected to assist in professional workflows, from AI research and engineeri…
Shared memory coordinates agents' actions, but correct records do not establish that those actions satisfy task requirem…
Mathematical problem solving often requires deterministic computational steps that agents delegate to tools and implicit…
Natural-language access to RDF knowledge graphs is a core Semantic Web ambition. Large language models (LLMs) have advan…
Developing reliable models for clinical tasks, such as Medical Question Answering (QA), is severely constrained by the l…
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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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LLM tool-use agents operate in dynamic environments where many actions carry operational risk.However, most safety mecha…
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Reinforcement learning with verifiable rewards (RLVR) turns agent experience into learning signals primarily through sca…
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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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LLM agents often lack the operational knowledge to act reliably in new environments, as they must discover specific tool…
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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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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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Tabular foundation models (TFMs) achieve strong predictive performance by conditioning on labeled demonstrations provide…
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Multimodal large language models have become the dominant paradigm for visual understanding, but incur substantial costs…
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