April 12, 2024, 4:42 a.m. | Ian Tenney, Ryan Mullins, Bin Du, Shree Pandya, Minsuk Kahng, Lucas Dixon

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.07498v1 Announce Type: cross
Abstract: We present Sequence Salience, a visual tool for interactive prompt debugging with input salience methods. Sequence Salience builds on widely used salience methods for text classification and single-token prediction, and extends this to a system tailored for debugging complex LLM prompts. Our system is well-suited for long texts, and expands on previous work by 1) providing controllable aggregation of token-level salience to the word, sentence, or paragraph level, making salience over long inputs tractable; and …

arxiv cs.ai cs.cl cs.hc cs.lg debugging interactive prompt type

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