SOTAVerified

Structured Prediction

Structured Prediction is an area of machine learning focusing on representations of spaces with combinatorial structure, and algorithms for inference and parameter estimation over these structures. Core methods include both tractable exact approaches like dynamic programming and spanning tree algorithms as well as heuristic techniques such as linear programming relaxations and greedy search.

Source: Torch-Struct: Deep Structured Prediction Library

Papers

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Showing 26–50 of 639 papers

TitleStatusHype
Towards Consistent Document-level Entity Linking: Joint Models for Entity Linking and Coreference ResolutionCode1
DEGREE: A Data-Efficient Generation-Based Event Extraction ModelCode1
Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale TasksCode1
Simple GNN Regularisation for 3D Molecular Property Prediction & BeyondCode1
Improving Pretrained Cross-Lingual Language Models via Self-Labeled Word AlignmentCode1
Energy-Based Learning for Scene Graph GenerationCode1
Structured Prediction as Translation between Augmented Natural LanguagesCode1
Assignment-Space-Based Multi-Object Tracking and SegmentationCode1
Group-Wise Semantic Mining for Weakly Supervised Semantic SegmentationCode1
A Frustratingly Easy Approach for Entity and Relation ExtractionCode1
Deep Structured Prediction for Facial Landmark DetectionCode1
On Long-Tailed Phenomena in Neural Machine TranslationCode1
Automated Concatenation of Embeddings for Structured PredictionCode1
Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement LearningCode1
Adversarial Attack and Defense of Structured Prediction ModelsCode1
Active Imitation Learning with Noisy GuidanceCode1
StructPool: Structured Graph Pooling via Conditional Random FieldsCode1
Instance-Based Learning of Span Representations: A Case Study through Named Entity RecognitionCode1
Structured Prediction with Partial Labelling through the Infimum LossCode1
Learning with Differentiable Perturbed OptimizersCode1
Estimating Gradients for Discrete Random Variables by Sampling without ReplacementCode1
LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured PredictionCode1
Structured Output Learning with Conditional Generative FlowsCode1
Learning Approximate Inference Networks for Structured PredictionCode1
Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level ConstraintsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified