Papers with FISH

2 papers
FISH: A Financial Interactive System for Signal Highlighting (2023.eacl-demo)

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Challenge: Existing systems or studies lack interactivity and do not provide off-the-shelf signals.
Approach: They propose an interactive system that extracts and highlights crucial financial signals . they integrate pre-trained BERT representations and a fine-tuned BERT highlighting model .
Outcome: The proposed system extracts and highlights key financial signals efficiently and precisely.
Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning (2023.emnlp-main)

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Challenge: Named Entity Recognition, Relation Extraction, Semantic Role Labeling are examples of sequence labeling problems that require finetuning to the target format.
Approach: They propose a dynamic sparse finetuning strategy that selectively focuses on a fraction of parameters, informed by feedback from highly regressing examples.
Outcome: The proposed approach improves performance in low-resource settings and in extreme low-level settings.

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