Goal-Oriented Dialogue Systems

12 papers with code • 0 benchmarks • 4 datasets

Achieving a pre-defined goal through a dialog.

Most implemented papers

Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models

snakeztc/NeuralDialog-LaRL NAACL 2019

Defining action spaces for conversational agents and optimizing their decision-making process with reinforcement learning is an enduring challenge.

Utterance-level Dialogue Understanding: An Empirical Study

declare-lab/dialogue-understanding 29 Sep 2020

Most of these approaches account for the context for effective understanding.

In-Context Learning User Simulators for Task-Oriented Dialog Systems

telepathylabsai/prompt-based-user-simulator 1 Jun 2023

This paper presents a novel application of large language models in user simulation for task-oriented dialog systems, specifically focusing on an in-context learning approach.

Sequential Dialogue Context Modeling for Spoken Language Understanding

sunbopds/SDEN-Pytorch-master WS 2017

We compare the performance of our proposed architecture with two context models, one that uses just the previous turn context and another that encodes dialogue context in a memory network, but loses the order of utterances in the dialogue history.

NIPS Conversational Intelligence Challenge 2017 Winner System: Skill-based Conversational Agent with Supervised Dialog Manager

sld/convai-bot-1337 COLING 2018

We present bot{\#}1337: a dialog system developed for the 1st NIPS Conversational Intelligence Challenge 2017 (ConvAI).

Incorporating Joint Embeddings into Goal-Oriented Dialogues with Multi-Task Learning

s6fikass/Chatbot_KVNN 28 Jan 2020

Since such models can greatly benefit from user intent and knowledge graph integration, in this paper we propose an RNN-based end-to-end encoder-decoder architecture which is trained with joint embeddings of the knowledge graph and the corpus as input.

A Fast and Robust BERT-based Dialogue State Tracker for Schema-Guided Dialogue Dataset

NVIDIA/NeMo 27 Aug 2020

Dialog State Tracking (DST) is one of the most crucial modules for goal-oriented dialogue systems.

Grounding Dialogue Systems via Knowledge Graph Aware Decoding with Pre-trained Transformers

SmartDataAnalytics/kgirnet 30 Mar 2021

Generating knowledge grounded responses in both goal and non-goal oriented dialogue systems is an important research challenge.

Maintaining Common Ground in Dynamic Environments

Alab-NII/dynamic-onecommon 29 May 2021

Common grounding is the process of creating and maintaining mutual understandings, which is a critical aspect of sophisticated human communication.