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 71–80 of 639 papers

TitleStatusHype
An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates—0
Doubly Reparameterized Importance Weighted Structure Learning for Scene Graph Generation—0
Query-Adaptive Predictive Inference with Partial Labels—0
Sort by Structure: Language Model Ranking as Dependency Probing—0
DeepSPIN: Deep Structured Prediction for Natural Language Processing—0
DOGE-Train: Discrete Optimization on GPU with End-to-end TrainingCode1
Importance Weighted Structure Learning for Scene Graph Generation—0
Learning Constrained Structured Spaces with Application to Multi-Graph MatchingCode0
Learning with Limited Text Data—0
Neural Structured Prediction for Inductive Node ClassificationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified