CAML meta-learns a progressively refined inductive bias from active-learning queries to improve robustness to spurious correlations, reporting accuracy gains on minority groups across several benchmarks.
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2026 2representative citing papers
Adapted MelBERT MIP-only reaches 0.7281 F1 on Chinese token-level metaphor detection, outperforming RoBERTa and Qwen QLoRA, with all artifacts released for reproducibility.
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Cumulative Meta-Learning from Active Learning Queries for Robustness to Spurious Correlations
CAML meta-learns a progressively refined inductive bias from active-learning queries to improve robustness to spurious correlations, reporting accuracy gains on minority groups across several benchmarks.
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A Reproducible Multi-Architecture Baseline for Token-Level Chinese Metaphor Identification under the MIPVU Framework
Adapted MelBERT MIP-only reaches 0.7281 F1 on Chinese token-level metaphor detection, outperforming RoBERTa and Qwen QLoRA, with all artifacts released for reproducibility.