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 521530 of 639 papers

TitleStatusHype
Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction0
Buy 4 REINFORCE Samples, Get a Baseline for Free!0
CaLcs: Continuously Approximating Longest Common Subsequence for Sequence Level Optimization0
Calibrating Structured Output Predictors for Natural Language Processing0
Candidate Constrained CRFs for Loss-Aware Structured Prediction0
Canonical Correlation Inference for Mapping Abstract Scenes to Text0
Capturing Dialogue State Variable Dependencies with an Energy-based Neural Dialogue State Tracker0
Classical Structured Prediction Losses for Sequence to Sequence Learning0
CLIP@UMD at SemEval-2016 Task 8: Parser for Abstract Meaning Representation using Learning to Search0
Closed-Form Training of Mahalanobis Distance for Supervised Clustering0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified