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 441–450 of 639 papers

TitleStatusHype
Using Context to Predict the Purpose of Argumentative Writing Revisions—0
Using word embedding for bio-event extraction—0
Utilizing Dependency Language Models for Graph-based Dependency Parsing Models—0
Vector-Valued Least-Squares Regression under Output Regularity Assumptions—0
Vine Pruning for Efficient Multi-Pass Dependency Parsing—0
Volume Optimality in Conformal Prediction with Structured Prediction Sets—0
Weakly-Supervised Semantic Segmentation of Circular-Scan, Synthetic-Aperture-Sonar Imagery—0
Weighting Finite-State Transductions With Neural Context—0
Word Reordering for Zero-shot Cross-lingual Structured Prediction—0
Polynomial-Time Exact MAP Inference on Discrete Models with Global Dependencies—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified