Papers by David Piorkowski

2 papers
Language Models in Dialogue: Conversational Maxims for Human-AI Interactions (2024.findings-emnlp)

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Challenge: Modern language models exhibit some inherent shortcomings, particularly in conversational settings.
Approach: They propose a set of maxims for describing effective human-AI conversation that include quantity, quality, relevance, manner, benevolence, and transparency.
Outcome: The proposed maxims are applied to human-AI interactions and are based on extensive research from the social science and AI communities.
Detecting Egregious Conversations between Customers and Virtual Agents (N18-1)

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Challenge: 80% of businesses plan to use chatbots by 2020, according to recent studies . but some bad conversations can be difficult to detect and could lead to litigation .
Approach: They propose a method to detect bad conversations using behavioral cues from the user and patterns in agent responses.
Outcome: The proposed method improves the detection F1 score by 20% over textual features.

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