| 1 |
NoRD: A Data-Efficient Vision-Language-Action Model that Drives without Reasoning |
提出NoRD以解决数据收集与推理标注成本高的问题 |
vision-language-action VLA |
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| 2 |
Predicting Sentence Acceptability Judgments in Multimodal Contexts |
研究视觉上下文对人类和LLM句子可接受性判断的影响 |
large language model multimodal |
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| 3 |
Physics-based phenomenological characterization of cross-modal bias in multimodal models |
提出基于物理的表征方法,分析多模态大语言模型中的跨模态偏差问题。 |
large language model multimodal |
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| 4 |
Multimodal MRI Report Findings Supervised Brain Lesion Segmentation with Substructures |
提出MS-RSuper方法,利用多模态MRI报告监督脑部病灶及其子结构的分割。 |
multimodal |
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| 5 |
E-MMKGR: A Unified Multimodal Knowledge Graph Framework for E-commerce Applications |
提出E-MMKGR:一个用于电商应用的统一多模态知识图谱框架 |
multimodal |
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| 6 |
Qwen-BIM: developing large language model for BIM-based design with domain-specific benchmark and dataset |
Qwen-BIM:构建领域特定大语言模型,用于BIM设计,并提出相应基准和数据集。 |
large language model |
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| 7 |
Modality-Guided Mixture of Graph Experts with Entropy-Triggered Routing for Multimodal Recommendation |
提出MAGNET模型,通过模态引导的图专家混合网络和熵触发路由,提升多模态推荐效果。 |
multimodal |
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| 8 |
Counterfactual Simulation Training for Chain-of-Thought Faithfulness |
提出反事实模拟训练(CST)以提升思维链(CoT)推理的可靠性。 |
chain-of-thought |
✅ |
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| 9 |
PromptCD: Test-Time Behavior Enhancement via Polarity-Prompt Contrastive Decoding |
PromptCD:极性提示对比解码,提升LLM/VLM测试时行为可控性 |
large language model visual grounding |
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| 10 |
A Benchmark for Deep Information Synthesis |
提出DEEPSYNTH基准,评估LLM智能体在复杂信息合成与推理任务中的能力。 |
large language model |
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| 11 |
SparkMe: Adaptive Semi-Structured Interviewing for Qualitative Insight Discovery |
SparkMe:自适应半结构化访谈,利用多智能体LLM进行定性洞察发现 |
large language model |
✅ |
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| 12 |
"Are You Sure?": An Empirical Study of Human Perception Vulnerability in LLM-Driven Agentic Systems |
首个大规模人类实验揭示LLM驱动Agent系统中Agent介导欺骗的脆弱性 |
large language model |
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| 13 |
LogicGraph : Benchmarking Multi-Path Logical Reasoning via Neuro-Symbolic Generation and Verification |
LogicGraph:提出神经符号生成与验证框架,用于评估多路径逻辑推理能力。 |
large language model |
✅ |
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| 14 |
Architecting AgentOS: From Token-Level Context to Emergent System-Level Intelligence |
提出AgentOS框架,将LLM重定义为推理内核,提升系统级智能 |
large language model |
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| 15 |
HELP: HyperNode Expansion and Logical Path-Guided Evidence Localization for Accurate and Efficient GraphRAG |
提出HELP框架,通过超节点扩展和逻辑路径引导,提升GraphRAG的准确性和效率 |
large language model |
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| 16 |
AdapTools: Adaptive Tool-based Indirect Prompt Injection Attacks on Agentic LLMs |
AdapTools:针对Agentic LLM的自适应工具型间接提示注入攻击 |
large language model |
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| 17 |
Grounding LLMs in Scientific Discovery via Embodied Actions |
EmbodiedAct:通过具身动作将LLM应用于科学发现,解决长时程模拟中的可靠性和稳定性问题。 |
large language model |
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| 18 |
Hybrid LLM-Embedded Dialogue Agents for Learner Reflection: Designing Responsive and Theory-Driven Interactions |
提出混合LLM嵌入式对话Agent,用于支持学习者反思,设计响应式和理论驱动的交互 |
large language model |
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