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 51–60 of 639 papers

TitleStatusHype
Exact Inference in High-order Structured Prediction—0
Backpropagation of Unrolled Solvers with Folded Optimization—0
Explaining Large Language Model-Based Neural Semantic Parsers (Student Abstract)—0
On the inconsistency of separable losses for structured prediction—0
Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization—0
Connecting the Dots: Floorplan Reconstruction Using Two-Level QueriesCode2
Lifting Weak Supervision To Structured PredictionCode0
Vector-Valued Least-Squares Regression under Output Regularity Assumptions—0
Prompting Language Models for Linguistic Structure—0
A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on GraphsCode0
Show:102550
← PrevPage 6 of 64Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified