Goal-Oriented Dialog

23 papers with code • 1 benchmarks • 6 datasets

Achieving a pre-defined goal through a dialog.

Most implemented papers

Learning End-to-End Goal-Oriented Dialog

facebookresearch/ParlAI 24 May 2016

We show similar result patterns on data extracted from an online concierge service.

Sequential Attention-based Network for Noetic End-to-End Response Selection

alibaba/esim-response-selection 9 Jan 2019

The noetic end-to-end response selection challenge as one track in Dialog System Technology Challenges 7 (DSTC7) aims to push the state of the art of utterance classification for real world goal-oriented dialog systems, for which participants need to select the correct next utterances from a set of candidates for the multi-turn context.

SUMBT: Slot-Utterance Matching for Universal and Scalable Belief Tracking

SKTBrain/SUMBT ACL 2019

In goal-oriented dialog systems, belief trackers estimate the probability distribution of slot-values at every dialog turn.

Query-Reduction Networks for Question Answering

uwnlp/qrn 14 Jun 2016

In this paper, we study the problem of question answering when reasoning over multiple facts is required.

Zero-Shot Dialog Generation with Cross-Domain Latent Actions

snakeztc/NeuralDialog-ZSDG WS 2018

This paper introduces zero-shot dialog generation (ZSDG), as a step towards neural dialog systems that can instantly generalize to new situations with minimal data.

Efficient Dialog Policy Learning via Positive Memory Retention

ruizhaogit/MNIST-GuessNumber 2 Oct 2018

This paper is concerned with the training of recurrent neural networks as goal-oriented dialog agents using reinforcement learning.

End-to-End Slot Alignment and Recognition for Cross-Lingual NLU

amazon-research/multiatis EMNLP 2020

We introduce MultiATIS++, a new multilingual NLU corpus that extends the Multilingual ATIS corpus to nine languages across four language families, and evaluate our method using the corpus.

Personalization in Goal-Oriented Dialog

chaitjo/personalized-dialog 22 Jun 2017

The main goal of modeling human conversation is to create agents which can interact with people in both open-ended and goal-oriented scenarios.

Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialog

naver/aqm-plus NeurIPS 2018

Goal-oriented dialogue tasks occur when a questioner asks an action-oriented question and an answerer responds with the intent of letting the questioner know a correct action to take.

NE-Table: A Neural key-value table for Named Entities

IBM/ne-table-datasets RANLP 2019

Many Natural Language Processing (NLP) tasks depend on using Named Entities (NEs) that are contained in texts and in external knowledge sources.