SOTAVerified

Dialogue Generation

Dialogue generation is the task of "understanding" natural language inputs - within natural language processing in order to produce output. The systems are usually intended for conversing with humans, for instance back and forth dialogue with a conversation agent like a chatbot. Some example benchmarks for this task (see others such as Natural Language Understanding) include FusedChat and Ubuntu DIalogue Corpus (UDC). Models can be evaluated via metrics such as BLEU, ROUGE, and METEOR albeit with challenges in terms of weak correlation with human judgement, that may be addressed by new ones like UnSupervised and Reference-free (USR) and Metric for automatic Unreferenced dialog evaluation (MaUde).

Papers

Showing 576600 of 606 papers

TitleStatusHype
Tailored Sequence to Sequence Models to Different Conversation Scenarios0
Knowledge Diffusion for Neural Dialogue GenerationCode0
Neural Text Generation in Stories Using Entity Representations as Context0
Automatic Dialogue Generation with Expressed EmotionsCode0
Self-Attention-Based Message-Relevant Response Generation for Neural Conversation Model0
Zero-Shot Dialog Generation with Cross-Domain Latent ActionsCode0
Modeling Psychotherapy Dialogues with Kernelized Hashcode Representations: A Nonparametric Information-Theoretic Approach0
Unsupervised Discrete Sentence Representation Learning for Interpretable Neural Dialog GenerationCode0
Improving Variational Encoder-Decoders in Dialogue Generation0
DP-GAN: Diversity-Promoting Generative Adversarial Network for Generating Informative and Diversified TextCode0
Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction0
Towards Interpretable Chit-chat: Open Domain Dialogue Generation with Dialogue Acts0
End-to-end Adversarial Learning for Generative Conversational AgentsCode0
Towards Automatic Generation of Entertaining Dialogues in Chinese Crosstalks0
Adversarial evaluation for open-domain dialogue generation0
Extended Named Entity Recognition API and Its Applications in Language Education0
Relevance of Unsupervised Metrics in Task-Oriented Dialogue for Evaluating Natural Language GenerationCode0
IDK Cascades: Fast Deep Learning by Learning not to Overthink0
Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational AutoencodersCode0
Data Distillation for Controlling Specificity in Dialogue Generation0
Latent Variable Dialogue Models and their DiversityCode0
Adversarial Learning for Neural Dialogue GenerationCode0
Deep Active Learning for Dialogue Generation0
Context-aware Natural Language Generation for Spoken Dialogue Systems0
Reference-Aware Language Models0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LMEDRAvg F121.99Unverified
2P^2 BotAvg F119.77Unverified
3TransferTransfoAvg F119.09Unverified
4Seq2Seq + AttentionAvg F116.18Unverified
5Synthesizer (R+V)BLEU-114.7Unverified
6KV Profile MemoryAvg F111.9Unverified
#ModelMetricClaimedVerifiedStatus
1Classification-based modelSlot Accuracy0.97Unverified
2Two-in-one modelSlot Accuracy0.97Unverified
#ModelMetricClaimedVerifiedStatus
1EVAmauve0.97Unverified
2Per-BOBmauve0.95Unverified
#ModelMetricClaimedVerifiedStatus
1mm1 in 10 R@25Unverified
#ModelMetricClaimedVerifiedStatus
1∞-former (Sticky memories)F19.01Unverified
#ModelMetricClaimedVerifiedStatus
1∞-former (Sticky memories + initialized GPT-2 Small)Perplexity32.48Unverified
#ModelMetricClaimedVerifiedStatus
1SpaceFusioninterest (human)2.53Unverified
#ModelMetricClaimedVerifiedStatus
1MrRNN Act.-Ent.F14.63Unverified
#ModelMetricClaimedVerifiedStatus
1MrRNN Act.-Ent.Accuracy34.48Unverified
#ModelMetricClaimedVerifiedStatus
1MrRNN Act.-Ent.F111.43Unverified
#ModelMetricClaimedVerifiedStatus
1MrRNN Act.-Ent.Accuracy95.04Unverified
#ModelMetricClaimedVerifiedStatus
1MrRNN Act.-Ent.F13.72Unverified
#ModelMetricClaimedVerifiedStatus
1MrRNN Act.-Ent.Accuracy29.01Unverified