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

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Showing 111–120 of 639 papers

TitleStatusHype
Reducing Model Churn: Stable Re-training of Conversational AgentsCode0
Coalescing Global and Local Information for Procedural Text UnderstandingCode0
Effectiveness of Function Matching in Driving Scene Recognition—0
SHARP: Search-Based Adversarial Attack for Structured Prediction—0
An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates—0
Doubly Reparameterized Importance Weighted Structure Learning for Scene Graph Generation—0
Query-Adaptive Predictive Inference with Partial Labels—0
Sort by Structure: Language Model Ranking as Dependency Probing—0
DeepSPIN: Deep Structured Prediction for Natural Language Processing—0
Importance Weighted Structure Learning for Scene Graph Generation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified