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
Assignment-Space-Based Multi-Object Tracking and SegmentationCode1
A Frustratingly Easy Approach for Entity and Relation ExtractionCode1
Fast and Accurate Entity Recognition with Iterated Dilated ConvolutionsCode1
Group-Wise Learning for Weakly Supervised Semantic SegmentationCode1
Group-Wise Semantic Mining for Weakly Supervised Semantic SegmentationCode1
Automated Concatenation of Embeddings for Structured PredictionCode1
Instance-Based Learning of Span Representations: A Case Study through Named Entity RecognitionCode1
Autoregressive Structured Prediction with Language ModelsCode1
Code4Struct: Code Generation for Few-Shot Event Structure PredictionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified