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 2130 of 639 papers

TitleStatusHype
Active Imitation Learning with Noisy GuidanceCode1
Energy-Based Learning for Scene Graph GenerationCode1
A Frustratingly Easy Approach for Entity and Relation ExtractionCode1
Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer NetworksCode1
Automated Concatenation of Embeddings for Structured PredictionCode1
Group-Wise Learning for Weakly Supervised Semantic SegmentationCode1
Learning to Repair: Repairing model output errors after deployment using a dynamic memory of feedbackCode1
Autoregressive Structured Prediction with Language ModelsCode1
Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement LearningCode1
Code4Struct: Code Generation for Few-Shot Event Structure PredictionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified