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 251–260 of 639 papers

TitleStatusHype
Outline Generation: Understanding the Inherent Content Structure of Documents—0
Prototypical Bregman Networks—0
Structured Prediction using cGANs with Fusion Discriminator—0
On the Use of ArXiv as a DatasetCode0
Personalized Bundle List Recommendation—0
Benchmarking Approximate Inference Methods for Neural Structured PredictionCode0
Learning to Stop in Structured Prediction for Neural Machine Translation—0
Neural Program Planner for Structured Predictions—0
Learning proposals for sequential importance samplers using reinforced variational inference—0
Multi-agent query reformulation: Challenges and the role of diversity—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified