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Found 9 papers, 5 papers with code
A Large Collection of Model-generated Contradictory Responses for Consistency-aware Dialogue Systems
In this paper, we build a large dataset of response generation models' contradictions for the first time.
Bipartite-play Dialogue Collection for Practical Automatic Evaluation of Dialogue Systems
Automation of dialogue system evaluation is a driving force for the efficient development of dialogue systems.
Target-Guided Open-Domain Conversation Planning
Prior studies addressing target-oriented conversational tasks lack a crucial notion that has been intensively studied in the context of goal-oriented artificial intelligence agents, namely, planning.
N-best Response-based Analysis of Contradiction-awareness in Neural Response Generation Models
In this scenario, the quality of the n-best list considerably affects the occurrence of contradictions because the final response is chosen from this n-best list.
Word Rotator's Distance
Accordingly, we propose a method that first decouples word vectors into their norm and direction, and then computes alignment-based similarity using earth mover's distance (i. e., optimal transport cost), which we refer to as word rotator's distance.
Evaluating Dialogue Generation Systems via Response Selection
Existing automatic evaluation metrics for open-domain dialogue response generation systems correlate poorly with human evaluation.
Filtering Noisy Dialogue Corpora by Connectivity and Content Relatedness
Large-scale dialogue datasets have recently become available for training neural dialogue agents.
Unsupervised Learning of Style-sensitive Word Vectors
This paper presents the first study aimed at capturing stylistic similarity between words in an unsupervised manner.
Generating Stylistically Consistent Dialog Responses with Transfer Learning
We propose a novel, data-driven, and stylistically consistent dialog response generation system.
