Search Results for author: Julian Killingback

Found 2 papers, 1 papers with code

SUBSUME: A Dataset for Subjective Summary Extraction from Wikipedia Documents

no code implementations EMNLP (newsum) 2021 Nishant Yadav, Matteo Brucato, Anna Fariha, Oscar Youngquist, Julian Killingback, Alexandra Meliou, Peter Haas

Several datasets exist for summarization with objective intents where, for each document and intent (e. g., “weather”), a single summary suffices for all users.

Extractive Summarization

Simulating Task-Oriented Dialogues with State Transition Graphs and Large Language Models

1 code implementation23 Apr 2024 Chris Samarinas, Pracha Promthaw, Atharva Nijasure, Hansi Zeng, Julian Killingback, Hamed Zamani

In our experiments, using graph-guided response simulations leads to significant improvements in intent classification, slot filling and response relevance compared to naive single-prompt simulated conversations.

Conversational Question Answering Dialogue State Tracking +8

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