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 221–230 of 639 papers

TitleStatusHype
Few-Shot Learning Through an Information Retrieval Lens—0
Findings of the 2012 Workshop on Statistical Machine Translation—0
Fast and Exact: ADMM-Based Discriminative Shape Segmentation with Loopy Part Models—0
Backpropagation of Unrolled Solvers with Folded Optimization—0
Capturing Dialogue State Variable Dependencies with an Energy-based Neural Dialogue State Tracker—0
Frame Semantics across Languages: Towards a Multilingual FrameNet—0
Fairness constraints can help exact inference in structured prediction—0
Extracting Relations between Non-Standard Entities using Distant Supervision and Imitation Learning—0
Canonical Correlation Inference for Mapping Abstract Scenes to Text—0
Explaining Large Language Model-Based Neural Semantic Parsers (Student Abstract)—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified