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 51–75 of 639 papers

TitleStatusHype
Code4Struct: Code Generation for Few-Shot Event Structure PredictionCode1
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal LearningCode1
Instance-Based Learning of Span Representations: A Case Study through Named Entity RecognitionCode1
Learning to Repair: Repairing model output errors after deployment using a dynamic memory of feedbackCode1
Estimation from Indirect Supervision with Linear MomentsCode0
A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on GraphsCode0
Evidence > Intuition: Transferability Estimation for Encoder SelectionCode0
A Probabilistic Generative Grammar for Semantic ParsingCode0
End-to-End Instance Segmentation with Recurrent AttentionCode0
Efficient Structured Inference for Transition-Based Parsing with Neural Networks and Error StatesCode0
Dr.VOT : Measuring Positive and Negative Voice Onset Time in the WildCode0
A Smoother Way to Train Structured Prediction ModelsCode0
Efficient Sub-structured Knowledge DistillationCode0
Experiment Segmentation in Scientific Discourse as Clause-level Structured Prediction using Recurrent Neural NetworksCode0
Beyond Data Samples: Aligning Differential Networks Estimation with Scientific KnowledgeCode0
Detect, Replace, Refine: Deep Structured Prediction For Pixel Wise LabelingCode0
Distilling Knowledge for Search-based Structured PredictionCode0
A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss EmbeddingsCode0
Abstract Meaning Representation Parsing using LSTM Recurrent Neural NetworksCode0
Dense and Low-Rank Gaussian CRFs Using Deep EmbeddingsCode0
Diverse Probabilistic Trajectory Forecasting with Admissibility ConstraintsCode0
Deep Structured Energy-Based Image InpaintingCode0
Active Learning amidst Logical KnowledgeCode0
Deep Sketched Output Kernel Regression for Structured PredictionCode0
Deep Structured Prediction with Nonlinear Output TransformationsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified