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
DOGE-Train: Discrete Optimization on GPU with End-to-end TrainingCode1
EncT5: A Framework for Fine-tuning T5 as Non-autoregressive ModelsCode1
Assignment-Space-Based Multi-Object Tracking and SegmentationCode1
Estimating Gradients for Discrete Random Variables by Sampling without ReplacementCode1
Adversarial Attack and Defense of Structured Prediction ModelsCode1
Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer NetworksCode1
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online LearningCode1
Autoregressive Structured Prediction with Language ModelsCode1
A Frustratingly Easy Approach for Entity and Relation ExtractionCode1
Automated Concatenation of Embeddings for Structured PredictionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified