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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 41–50 of 639 papers

TitleStatusHype
Group-Wise Semantic Mining for Weakly Supervised Semantic SegmentationCode1
Improving Pretrained Cross-Lingual Language Models via Self-Labeled Word AlignmentCode1
Active Imitation Learning with Noisy GuidanceCode1
Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement LearningCode1
Learning Approximate Inference Networks for Structured PredictionCode1
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal LearningCode1
Automated Concatenation of Embeddings for Structured PredictionCode1
A Frustratingly Easy Approach for Entity and Relation ExtractionCode1
MvP: Multi-view Prompting Improves Aspect Sentiment Tuple PredictionCode1
DEGREE: A Data-Efficient Generation-Based Event Extraction ModelCode1
Show:102550
← PrevPage 5 of 64Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified