Dolph2Vec is the first species-specific self-supervised model for dolphin vocalizations, trained on longitudinal recordings from five dolphins, that outperforms general baselines on signature whistle classification and detection while producing embeddings aligned with known whistle categories.
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7 Pith papers cite this work, alongside 4 external citations. Polarity classification is still indexing.
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Pith papers citing it
4
external citations · external index
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2026 7verdicts
UNVERDICTED 7roles
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A critical discourse analysis of 200 YouTube software engineering tutorials finds male characters and masculine defaults dominate, with an agency gap assigning technical roles almost exclusively to males.
CIR is a cross-platform container image format for Python/R-style apps that defers dependency assembly to deployment, cutting image size by 95% and deployment time by 40-60% versus traditional bundled images.
LIP decomposes GNN message passing to quantify label influences, builds a label influence graph, and propagates high-order effects to outperform prior methods on multi-label node classification benchmarks.
Learnable graph patches enable domain-agnostic pre-training of graph models by decomposing heterogeneous graphs into transferable semantic units via patch encoders and aggregators.
Proposes a heterogeneous quantum repeater network architecture using recursive designs and RuleSets with a new bridging building block, but states that full-scale resource trade-off analysis remains future work.
ReCoG is a context graph learning framework with relational learning and information bottleneck modules for few-shot molecular property prediction.
citing papers explorer
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Dolph2Vec: Self-Supervised Representations of Dolphin Vocalizations
Dolph2Vec is the first species-specific self-supervised model for dolphin vocalizations, trained on longitudinal recordings from five dolphins, that outperforms general baselines on signature whistle classification and detection while producing embeddings aligned with known whistle categories.
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A Critical Discourse Analysis of Gender Representation in Software Engineering Education Videos on YouTube
A critical discourse analysis of 200 YouTube software engineering tutorials finds male characters and masculine defaults dominate, with an agency gap assigning technical roles almost exclusively to males.
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CIR: Lightweight Container Image for Cross-Platform Deployment
CIR is a cross-platform container image format for Python/R-style apps that defers dependency assembly to deployment, cutting image size by 95% and deployment time by 40-60% versus traditional bundled images.
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Multi-Label Node Classification with Label Influence Propagation
LIP decomposes GNN message passing to quantify label influences, builds a label influence graph, and propagates high-order effects to outperform prior methods on multi-label node classification benchmarks.
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Handling Feature Heterogeneity with Learnable Graph Patches
Learnable graph patches enable domain-agnostic pre-training of graph models by decomposing heterogeneous graphs into transferable semantic units via patch encoders and aggregators.
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Resource Management in Heterogeneous Quantum Repeater Networks
Proposes a heterogeneous quantum repeater network architecture using recursive designs and RuleSets with a new bridging building block, but states that full-scale resource trade-off analysis remains future work.
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ReCoG: Relational and Compact Context Graph Learning for Few-shot Molecular Property Prediction
ReCoG is a context graph learning framework with relational learning and information bottleneck modules for few-shot molecular property prediction.