Structured Prediction
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Benchmarks
MNIST
Most implemented
Convolutional Pose Machines
VSE++: Improving Visual-Semantic Embeddings with Hard Negatives
Neural Networks for Joint Sentence Classification in Medical Paper Abstracts
ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation
Papers
From Rules to Neural Graphs: Scalable Structured Prediction for Patent Prior Art Search
Patent search requires processing documents routinely exceeding tens of thousands of tokens. Most neural retrieval approaches operate on truncated inputs, limiting their effectiveness. Graph-based retrieval addresses thi…
Structured PredictionDependency ParsingHard Vision, Easy Vision: What GPT-6 Astra Reveals Across Computer Vision
Frontier general-purpose systems are rapidly expanding beyond visual understanding into capabilities traditionally handled by dedicated computer-vision models. As these capabilities expand, a central question for the com…
Structured PredictionSpatial ReasoningNeuro-Symbolic Hierarchical Intention Anticipation in Human Behavior
Assistive autonomous systems must anticipate human goals before an observed behavior is complete. This article formulates anticipation as goal inference from a partially observed multimodal episode together with structur…
Structured PredictionKey Point Analysis Needs Structure Recovery: Task Definition, Dataset Diagnosis, and a Structure-Aware Benchmark
Key Point Analysis (KPA) aims to identify a concise set of key points that summarize a collection of arguments together with their prevalence. We argue that KPA is fundamentally a structured prediction problem that requi…
Structured PredictionA Simulator-Grounded Framework For Constructing Verifiable Muscle-Grounded QA From 3D Tongue Meshes (extended version)
Existing articulatory corpora based on real-time MRI and electromagnetic articulography capture tongue motion but lack traceable labels for the muscle-driven process underlying each configuration. We introduce a simulato…
Structured PredictionWhen Machines Speak: A Unified Generative Framework for Integrating Machine-Native Symbols into Pretrained Large Language Models
Many real-world AI systems represent entities, behaviors, and structured information using discrete machine-native symbols rather than natural language. While these representations are compact and preserve task-relevant …
Sequential RecommendationStructured Prediction