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Despite the rise of LLMs, structured linguistic features and simple fusion-based classifiers still outperform them in low-data cognitive impairment detection across multiple languages.
Forget English: LLMs can now reliably extract ESG sentiment from Slovene news, opening doors for automated analysis in overlooked markets.
Achieve massive gains in few-shot hierarchical multi-label classification (+42%) by adaptively balancing semantic priors and visual evidence using level-aware embeddings.
Guaranteeing connectivity in text embedding graphs with a simple incremental construction unlocks more robust and parameter-insensitive spectral clustering.
