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Found 3 papers, 2 papers with code
TA&AT: Enhancing Task-Oriented Dialog with Turn-Level Auxiliary Tasks and Action-Tree Based Scheduled Sampling
Specifically, we model the hierarchical policy as trees and utilize the similarity between trees to sample negative policy based on scheduled sampling, hoping the model to generate invariant responses under perturbations.
Channel-aware Decoupling Network for Multi-turn Dialogue Comprehension
We decouple the contextualized word representations by masking mechanisms in Transformer-based PrLM, making each word only focus on the words in current utterance, other utterances, and two speaker roles (i. e., utterances of sender and utterances of the receiver), respectively.
Filling the Gap of Utterance-aware and Speaker-aware Representation for Multi-turn Dialogue
A multi-turn dialogue is composed of multiple utterances from two or more different speaker roles.
