Nonlinear polynomial models fit local paraphrase embedding clouds more accurately than linear ones and support geometrically consistent synthetic point generation, yet this geometric fidelity does not improve classification performance.
and Dagan, I.Still a pain in the neck: Evaluating Text Representations on Lexical Composition
2 Pith papers cite this work. Polarity classification is still indexing.
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SemanticQA unifies prior multiword expression datasets into a benchmark that reveals substantial performance variation among language models on semantic reasoning tasks.
citing papers explorer
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Controlled Paraphrase Geometry in Sentence Embedding Space: Local Manifold Modeling and Latent Probing
Nonlinear polynomial models fit local paraphrase embedding clouds more accurately than linear ones and support geometrically consistent synthetic point generation, yet this geometric fidelity does not improve classification performance.
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Revisiting a Pain in the Neck: A Semantic Reasoning Benchmark for Language Models
SemanticQA unifies prior multiword expression datasets into a benchmark that reveals substantial performance variation among language models on semantic reasoning tasks.