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 1120 of 639 papers

TitleStatusHype
A Frustratingly Easy Approach for Entity and Relation ExtractionCode1
DOGE-Train: Discrete Optimization on GPU with End-to-end TrainingCode1
Energy-Based Learning for Scene Graph GenerationCode1
Estimating Gradients for Discrete Random Variables by Sampling without ReplacementCode1
CrossBeam: Learning to Search in Bottom-Up Program SynthesisCode1
Automated Concatenation of Embeddings for Structured PredictionCode1
Adversarial Attack and Defense of Structured Prediction ModelsCode1
Autoregressive Structured Prediction with Language ModelsCode1
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online LearningCode1
Assignment-Space-Based Multi-Object Tracking and SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified