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 110 of 639 papers

TitleStatusHype
An Expression Tree Decoding Strategy for Mathematical Equation GenerationCode2
Connecting the Dots: Floorplan Reconstruction Using Two-Level QueriesCode2
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP ModelsCode2
Torch-Struct: Deep Structured Prediction LibraryCode2
Torch-Struct: Deep Structured Prediction LibraryCode2
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal LearningCode1
Meaning Typed Prompting: A Technique for Efficient, Reliable Structured Output GenerationCode1
SpEL: Structured Prediction for Entity LinkingCode1
SPEECH: Structured Prediction with Energy-Based Event-Centric HyperspheresCode1
MvP: Multi-view Prompting Improves Aspect Sentiment Tuple PredictionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified