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HydraPrompt: An Adaptive and Asymmetric Framework of Vision-Language Models for Synthetic Image Detection Geometry-Aware Representation Denoising for Robust Multi-view 3D Reconstruction 3D Gaussian Map with Open-Set Semantic Grouping for Vision-Language Navigation On the Push-Based Asynchronous Federated Learning: A Bias-Correction Aggregation Approach OmniInteract: Benchmarking Real-World Streaming Interaction for Real-Time Omnimodal Assistants CNNs, Transformers, Hybrid, and Vision Language Models for Skin Cancer Detection VesselSim: learning 3D blood vessel segmentation without expert annotations Erased but Exploitable: Black-box Embedding-Aware Prompting Against Unlearned Text-to-Image Diffusion Models VisualNeedle: Benchmarking Active Visual Search in Information-Dense Scenes DuoGesture: Neuro-Inspired and Biomechanically Informed Dual-Stream Co-Speech Gesture Generation RadarSim: Simulating Single-Chip Radar via Multimodal Neural Fields RoMo: A Large-Scale, Richly Organized Dataset and Semantic Taxonomy for Human Motion Generation The Rescue Effect: Spatio-Semantic Early Exit Bypasses Quantization Collapse in CLIP When Rule Violations Are Rare: Chimera Training for Logical Anomaly Detection Detail Consistent Stage-Wise Distillation for Efficient 3D MRI Segmentation Sparse-LiDAR Prompting of Monocular Geometry Foundations: An Empirical Study Toward Long-Range Driving Depth AirCast-SR: A Foundation Model for Kilometer-Scale Atmospheric Super-Resolution via Latent Consistency Diffusion Personalized Generative Models for Contextual Debiasing Cross-scale Aligned Supervision for Training GANs Joint Instance Segmentation and Geometric Attribute Regression for Roof Structures in Aerial Imagery Dimensional Distribution Emotion State: Leveraging Valence and Arousal as a Common Embedding Space for Visual Emotion Analysis TSFMAudit: Data Contamination Auditing in Forecasting Time Series Foundation Models Clinically-Grounded Counterfactual Reasoning for Medical Video Diagnosis Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules Comparative Study of Vision-Based Metric Measurement for Large-Scale Planar Scenes LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV The Constraint Tax: Measuring Validity-Correctness Tradeoffs in Structured Outputs for Small Language Models SilIF: Silhouette-Augmented Isolation Forest for Unsupervised Transaction Fraud Detection Multi-Modal Building Inspection via Perceiver IO Fusion of Satellite and Street-Level Imagery E$^3$C: Video Generation with 3D Environmental Memory and Ego-Exo Human Pose Control Share More, Search Less: Collaborative Parallel Thinking for Efficient Test-Time Scaling Unveiling the Fragility of Vision-Language Models: Multi-Modal Adversarial Synergy via Texture-Constrained Perturbations and Cross-Modal Optimization Sleep-stage efficient classification using a lightweight self-supervised model Underwater360: Reconstructing Underwater Scenes from Panoramic Images with Omnidirectional Gaussian Splatting Rethinking Weakly-supervised Video Temporal Grounding From a Game Perspective Sentinel: Embodied Cooperative Spatial Reasoning and Planning LongCat-Video-Avatar 1.5 Technical Report GEM: Geometric Entropy Mixing for Optimal LLM Data Curation Uncertainty-Aware Gaussian Map for Vision-Language Navigation Frequency-Guided Fusion For RGB-Thermal Semantic Segmentation BioFact-MoE: Biologically Factorized Mixture of Experts for Vision-Language Prognostic Modeling in Hepatocellular Carcinoma A multifractal-based masked auto-encoder: an application to medical images Benchmarking Convolutional, Transformer, Hybrid, and Vision Language Models for Multi Disease Retinal Screening Unified Panoramic Geometry Estimation via Multi-View Foundation Models Not All Modalities Are Equal: Instruction-Aware Gating for Multimodal Videos OmniGF: A Dual-Branch Vision-Language Framework for Unified Gaze Following Zero-Shot Object Re-Identification in Egocentric Kitchen Videos via Multi-Stage SAM3 Feature Fusion Evi-Steer: Learning to Steer Biomedical Vision-Language Models through Efficient and Generalizable Evidential Tuning Planning Neural Dynamics with Lie Group Embedding through Supervised Projective Manifold Learning AnchorDiff: Training-Free Concept Grounding for MM-DiTs via Anchor-Based Graph Propagation
何故大语言模型于结构知识上幻象?线性化表征推理之机理性分析
Shanghao Li, · 2026-05-27 · via cs updates on arXiv.org

观PDF HTML(实验性)

摘要:于多般推理之务,大语言模型(LLMs)常恃结构外知,如图谱与表格,此等知识多线性化为序列符码之表。然纵有足够能知,LLMs犹能生幻象之输出,而其下之机制,人犹未明。吾等究其机,乃知幻象起于系统内动,非偶然之噪。其一,注力偏重于捷径类之结构微候,而非遍及全境。其二,前馈表征未能固其所知,致模型复归参数之忆。复次,吾等之果示幻象恒与前馈层语义固之失相随,而注力之配则显任务相异之变。终,吾等示此机制之模,可越单跳图谱,及于多跳与表格之境,使于结构知识之式,得有效察幻象。
评述: 载于 ACL 2026 论文集
主题: 计算语言学 (cs.CL);人工智能 (cs.AI)
报告 编号: ACL 2026
引文格式: arXiv:2605.26362 [cs.CL]
  (或 arXiv:2605.26362v1 [cs.CL]为此版本之用)
  https://doi.org/10.48550/arXiv.2605.26362

arXiv所颁DOI,经DataCite(待注册)

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