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

Showing 4150 of 639 papers

TitleStatusHype
Instance-Based Learning of Span Representations: A Case Study through Named Entity RecognitionCode1
Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement LearningCode1
Active Imitation Learning with Noisy GuidanceCode1
Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer NetworksCode1
Learning with Differentiable Perturbed OptimizersCode1
LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured PredictionCode1
Energy-Based Learning for Scene Graph GenerationCode1
A Frustratingly Easy Approach for Entity and Relation ExtractionCode1
NeuralTailor: Reconstructing Sewing Pattern Structures from 3D Point Clouds of GarmentsCode1
Group-Wise Semantic Mining for Weakly Supervised Semantic SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified