Declarative logic programs offer a powerful and interpretable abstraction for encoding relational structure and neurosym…
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Understanding large language model (LLM) reasoning requires looking beyond behavioral performance to examine how reasoni…
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Learning and problem solving depend critically on the structure of internal representations.While many modern data-drive…
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Large language model compliance systems are deployed on the assumption that a verdict depends on the regulatory rule it…
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Do LLM scientific agents rely only on their initial task context, or do they adapt their decisions in response to experi…
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Randomized controlled trials (RCTs) identify treatment effects without confounding but are often small, whereas observat…
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Accurate simulation of rigid-body interactions is essential for predictive physical world models.Despite recent progress…
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Anatomical continuity provides complementary information for medical image restoration, but its use requires accounting…
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Adversarial games have driven advances from heuristic search to reinforcement learning, yet learning and adapting strate…
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Supervised fine-tuning (SFT) adapts pretrained large language models (LLMs) to downstream tasks, but the required concep…
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Spatial reasoning remains a persistent weakness of vision-language models (VLMs), because RGB inputs do not directly pro…
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When retrieved evidence contradicts an agent's prior beliefs, does it revise its answer, acknowledge uncertainty, or per…
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Large language models increasingly justify legal decisions by naming the statute or precedent behind a verdict, treated…
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Intelligent grading and automated scoring technologies constitute critical infrastructure for smart education.However, e…
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Agents are deployed in applications from trip planners and stock trading to IT incident triage.In most cases, LLM agents…
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The prevailing approach to improving robot foundation models (RFMs) relies on larger models, more robot demonstrations,…
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Multimodal large language models (MLLMs) often struggle to identify and use geometric relations in diagrams.Recent metho…
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Self-supervised multimodal representation learning has achieved remarkable success across diverse domains, yet capturing…
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Current 3D generation methods lack explicit local control: geometric adherence is often defined by a global control stre…
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World action models (WAMs) predict actions and future observations, typically from a reconstruction-based representation…
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