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 251–275 of 639 papers

TitleStatusHype
Learning to Stop in Structured Prediction for Neural Machine Translation—0
Neural Program Planner for Structured Predictions—0
Buy 4 REINFORCE Samples, Get a Baseline for Free!—0
Multi-agent query reformulation: Challenges and the role of diversity—0
Learning proposals for sequential importance samplers using reinforced variational inference—0
Structured Knowledge Distillation for Dense PredictionCode0
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction—0
Perturbation Based Learning for Structured NLP Tasks with Application to Dependency Parsing—0
Scaling Matters in Deep Structured-Prediction Models—0
A Smoother Way to Train Structured Prediction ModelsCode0
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling—0
A General Theory for Structured Prediction with Smooth Convex Surrogates—0
Learning Hierarchical Interactions at Scale: A Convex Optimization ApproachCode0
Extracting Multiple-Relations in One-Pass with Pre-Trained TransformersCode0
Geometric Matrix Completion with Deep Conditional Random Fields—0
Learning with Fenchel-Young LossesCode0
Search-Guided, Lightly-supervised Training of Structured Prediction Energy Networks—0
Compact Representation of Uncertainty in Clustering—0
Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses—0
Improved Dynamic Memory Network for Dialogue Act Classification with Adversarial Training—0
Distributionally Robust Graphical Models—0
Approximate Dynamic Oracle for Dependency Parsing with Reinforcement Learning—0
Feasible Annotation Scheme for Capturing Policy Argument Reasoning using Argument TemplatesCode0
Learning Beam Search Policies via Imitation LearningCode0
Deep Structured Prediction with Nonlinear Output TransformationsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified