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 61–70 of 639 papers

TitleStatusHype
A Fenchel-Young Loss Approach to Data-Driven Inverse Optimization—0
Learning Differentiable Surrogate Losses for Structured Prediction—0
Conformal Structured PredictionCode0
Understanding the Effect of Algorithm Transparency of Model Explanations in Text-to-SQL Semantic Parsing—0
Sigma Flows for Image and Data Labeling and Learning Structured Prediction—0
Structured Prediction in Online Learning—0
Deep Sketched Output Kernel Regression for Structured PredictionCode0
To be Continuous, or to be Discrete, Those are Bits of QuestionsCode0
CF-OPT: Counterfactual Explanations for Structured PredictionCode0
HYSYNTH: Context-Free LLM Approximation for Guiding Program Synthesis—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified