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 91–100 of 639 papers

TitleStatusHype
Linear-Time Modeling of Linguistic Structure: An Order-Theoretic Perspective—0
Data-efficient Active Learning for Structured Prediction with Partial Annotation and Self-Training—0
Modified Gauss-Newton Algorithms under Noise—0
Mixture of Soft Prompts for Controllable Data GenerationCode0
Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with KernelsCode0
PAC Prediction Sets for Large Language Models of CodeCode0
Diverse Probabilistic Trajectory Forecasting with Admissibility ConstraintsCode0
Exact Inference in High-order Structured Prediction—0
Backpropagation of Unrolled Solvers with Folded Optimization—0
Explaining Large Language Model-Based Neural Semantic Parsers (Student Abstract)—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified