LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction
Table 3: NLI accuracy scores with structured attention. The LP-SparseMAP models perform competitively.
['[EMPTY]', 'SNLI valid', 'SNLI test', 'MultiNLI valid', 'MultiNLI test']
On both datasets, the relaxed LP-matching outperforms the coarse matching factor, suggesting that, indeed, equivalent parametrizations of a model may perform differently when not run until convergence.