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 311–320 of 639 papers

TitleStatusHype
Portuguese Named Entity Recognition using Conditional Random Fields and Local Grammars—0
Posterior regularization for Joint Modeling of Multiple Structured Prediction Tasks with Soft Constraints—0
Pre- and In-Parsing Models for Neural Empty Category Detection—0
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction—0
Predicting deliberative outcomes—0
Predicting deliberative outcomes—0
Predicting Structures in NLP: Constrained Conditional Models and Integer Linear Programming in NLP—0
Predicting Through Generation: Why Generation Is Better for Prediction—0
Predictive Inference with Weak Supervision—0
Priberam: A Turbo Semantic Parser with Second Order Features—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified