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 321–330 of 639 papers

TitleStatusHype
Energy Disaggregation with Semi-supervised Sparse Coding—0
Ensemble Distillation for Structured Prediction: Calibrated, Accurate, Fast-Choose Three—0
Entropy-Based Latent Structured Output Prediction—0
Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces—0
Exact Inference in High-order Structured Prediction—0
Experiments with crowdsourced re-annotation of a POS tagging data set—0
Explaining Fast Improvement in Online Imitation Learning—0
Explaining Large Language Model-Based Neural Semantic Parsers (Student Abstract)—0
Extracting Relations between Non-Standard Entities using Distant Supervision and Imitation Learning—0
Fairness constraints can help exact inference in structured prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified