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

Showing 2130 of 639 papers

TitleStatusHype
Leveraging Linguistically Enhanced Embeddings for Open Information Extraction0
Trading off Consistency and Dimensionality of Convex Surrogates for the Mode0
Structured Language Generation Model for Robust Structure Prediction0
Online Structured Prediction with Fenchel--Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss0
Weakly-Supervised Semantic Segmentation of Circular-Scan, Synthetic-Aperture-Sonar Imagery0
Promptly Predicting Structures: The Return of InferenceCode0
Lazy-k: Decoding for Constrained Token ClassificationCode0
Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse FinetuningCode0
SpEL: Structured Prediction for Entity LinkingCode1
A Unified View of Evaluation Metrics for Structured PredictionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified