[PDF] Top 20 Adversarial evaluation for open domain dialogue generation
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Adversarial evaluation for open domain dialogue generation
... We test the discriminator on the same data and compare its performance to the human judge- ments. Chance level accuracy for both humans and the discriminator is 50%, namely when real and fake passages are ... See full document
5
Open domain Utterance Generation for Conversational Dialogue Systems using Web scale Dependency Structures
... though open-domain conversational dialogue systems are required in many fields, their development is complicated because of the flexibility and variety of user ...Our open-domain ... See full document
5
Open Domain Why Question Answering with Adversarial Learning to Encode Answer Texts
... Our evaluation against a Japanese open-domain why-QA dataset, which was created using general web texts as a source of answer passages, revealed that the generator net- work significantly improved ... See full document
11
Adversarial Domain Adaptation Using Artificial Titles for Abstractive Title Generation
... source domain to an unlabeled target domain in the context of an encoder-decoder model for text ...to adversarial domain adaptation (ADA), we introduce the use of artificial titles and ... See full document
7
Scalable and Accurate Dialogue State Tracking via Hierarchical Sequence Generation
... incorporating open vocabulary and copy mechanism for explicit un- seen words generation, and inventing better dia- logue history access mechanism to accommodate efficient inter-turn ... See full document
10
System Utterance Generation by Label Propagation over Association Graph of Words and Utterance Patterns for Open-Domain Dialogue Systems
... for dialogue sys- tems to automatically generate chat responses be- cause of the wide variety of topics in user utter- ...ordinary dialogue systems, ... See full document
9
Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning
... of adversarial dialogue generation models relies on the quality of the reward signal produced by the ...proposed adversarial dialogue generation method to an adversarial ... See full document
8
Investigating Evaluation of Open Domain Dialogue Systems With Human Generated Multiple References
... Multiple hypotheses were generated from all the models. For CVAE, multiple responses are sam- pled from the latent space with greedy word-level decoding. For rest of the generation models, five responses were ... See full document
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SlugNERDS: A Named Entity Recognition Tool for Open Domain Dialogue Systems
... structured dialogue system will be able to pick the contextually relevant entity for follow-up questions and ig- nore extraneous entities which may have been misclassi- ...empirical evaluation we have ... See full document
8
Multi domain Neural Network Language Generation for Spoken Dialogue Systems
... Human evaluation for utterance quality in two ...target domain data (DT-10%), adapting with ML training but only 10% of target domain data (ML-10%), and training from scratch using only 10% of target ... See full document
10
Improving Open Domain Dialogue Systems via Multi Turn Incomplete Utterance Restoration
... The n-gram restoration score proposed in Sec- tion 3.3 is adopted as the automatic evaluation metrics. Then human evaluation is further con- ducted. Specifically, human annotators are in- structed to ... See full document
10
ViGGO: A Video Game Corpus for Data To Text Generation in Open Domain Conversation
... guage generation (NLG) led to the release of both small and relatively large parallel corpora for training neural ...oriented dialogue systems, and often thus lim- ited in diversity and ...conversational ... See full document
9
Answer guided and Semantic Coherent Question Generation in Open domain Conversation
... The conditional variational autoencoder (C- VAE) (Sohn et al., 2015) is an extention of sequence-to-sequence model, and proves to be very effective in promoting the diversity in conver- sation generation (Serban ... See full document
11
Better Automatic Evaluation of Open Domain Dialogue Systems with Contextualized Embeddings
... in open-domain dialogue systems, automatic evaluation of such systems is still a challenging ...Blended Evaluation Rou- tine (RUBER) to combine a learning-based metric, which predicts ... See full document
8
Multi turn Dialogue Response Generation in an Adversarial Learning Framework
... an adversarial learning approach for generating multi-turn dialogue ...generative adversarial networks ...the dialogue history are used to perturb the generator’s latent space to generate sev- ... See full document
12
DAL: Dual Adversarial Learning for Dialogue Generation
... years, open-domain dialogue systems are gaining much attention owing to their great po- tential in applications such as educational robots, emotional companion, and ...for open-domain ... See full document
10
Adversarial Learning for Neural Dialogue Generation
... for open-domain dialogue gen- eration: the system is trained to pro- duce sequences that are indistinguish- able from human-generated dialogue ut- ... See full document
13
Answering Complex Open domain Questions Through Iterative Query Generation
... Multi-hop QA datasets QAngaroo (Welbl et al., 2018) and H OTPOT QA (Yang et al., 2018) are among the largest-scale multi-hop QA datasets to date. While the former is constructed around a knowledge base and the knowledge ... See full document
13
Plan, Write, and Revise: an Interactive System for Open Domain Story Generation
... Swanson and Gordon (2009) use an informa- tion retrieval based system to write by alternating turns between a human and their system. Clark and Smith (2018) use a similar turn-taking ap- proach to interactivity, but ... See full document
9
Transferable End to End Aspect based Sentiment Analysis with Selective Adversarial Learning
... unsupervised domain adap- tation setting for this ...Selective Adversarial Learning (SAL) method to align the inferred correla- tion vectors that automatically capture their latent ... See full document
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