Dialogue Management
24 papers with code • 0 benchmarks • 1 datasets
( Image credit: Bocklisch et al. )
Benchmarks
These leaderboards are used to track progress in Dialogue Management
DialoGLUE
Latest papers with no code
Thread Detection and Response Generation using Transformers with Prompt Optimisation
To address these challenges an end-to-end model that identifies threads and prioritises their response generation based on the importance was developed, involving a systematic decomposition of the problem into discrete components - thread detection, prioritisation, and performance optimisation which was meticulously analysed and optimised.
Illuminate: A novel approach for depression detection with explainable analysis and proactive therapy using prompt engineering
This paper introduces a novel paradigm for depression detection and treatment using advanced Large Language Models (LLMs): Generative Pre-trained Transformer 4 (GPT-4), Llama 2 chat, and Gemini.
OmniDialog: An Omnipotent Pre-training Model for Task-Oriented Dialogue System
Furthermore, to glean a nuanced understanding of OmniDialog's strengths and potential pitfalls, we designed a fine-grained analysis framework for dialogue-centric tasks.
Towards a Neural Era in Dialogue Management for Collaboration: A Literature Survey
Dialogue-based human-AI collaboration can revolutionize collaborative problem-solving, creative exploration, and social support.
Leveraging Large Language Models in Conversational Recommender Systems
A Conversational Recommender System (CRS) offers increased transparency and control to users by enabling them to engage with the system through a real-time multi-turn dialogue.
Multi-Task End-to-End Training Improves Conversational Recommendation
In this paper, we analyze the performance of a multitask end-to-end transformer model on the task of conversational recommendations, which aim to provide recommendations based on a user's explicit preferences expressed in dialogue.
Ericson: An Interactive Open-Domain Conversational Search Agent
Open-domain conversational search (ODCS) aims to provide valuable, up-to-date information, while maintaining natural conversations to help users refine and ultimately answer information needs.
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management
By exploiting MoE-LM structure, our methods significantly reduce the size of the action space and improve the efficacy of RL-based DM.
Parameter-Efficient Low-Resource Dialogue State Tracking by Prompt Tuning
Dialogue state tracking (DST) is an important step in dialogue management to keep track of users' beliefs.
A Survey on Conversational Search and Applications in Biomedicine
This paper aims to provide a radical rundown on Conversation Search (ConvSearch), an approach to enhance the information retrieval method where users engage in a dialogue for the information-seeking tasks.
