Neural approaches to conversational AI
This tutorial surveys neural approaches to conversational AI that were developed in the last
few years. We group conversational systems into three categories:(1) question answering …
few years. We group conversational systems into three categories:(1) question answering …
A survey on empathetic dialogue systems
Dialogue systems have achieved growing success in many areas thanks to the rapid
advances of machine learning techniques. In the quest for generating more human-like …
advances of machine learning techniques. In the quest for generating more human-like …
[HTML][HTML] Bridging the gap: A survey on integrating (human) feedback for natural language generation
Natural language generation has witnessed significant advancements due to the training of
large language models on vast internet-scale datasets. Despite these advancements, there …
large language models on vast internet-scale datasets. Despite these advancements, there …
A simple language model for task-oriented dialogue
Task-oriented dialogue is often decomposed into three tasks: understanding user input,
deciding actions, and generating a response. While such decomposition might suggest a …
deciding actions, and generating a response. While such decomposition might suggest a …
Dress: Instructing large vision-language models to align and interact with humans via natural language feedback
We present DRESS a large vision language model (LVLM) that innovatively exploits Natural
Language feedback (NLF) from Large Language Models to enhance its alignment and …
Language feedback (NLF) from Large Language Models to enhance its alignment and …
Galaxy: A generative pre-trained model for task-oriented dialog with semi-supervised learning and explicit policy injection
Pre-trained models have proved to be powerful in enhancing task-oriented dialog systems.
However, current pre-training methods mainly focus on enhancing dialog understanding …
However, current pre-training methods mainly focus on enhancing dialog understanding …
Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback
Large language models (LLMs) are used to generate content for a wide range of tasks, and
are set to reach a growing audience in coming years due to integration in product interfaces …
are set to reach a growing audience in coming years due to integration in product interfaces …
Way off-policy batch deep reinforcement learning of implicit human preferences in dialog
Most deep reinforcement learning (RL) systems are not able to learn effectively from off-
policy data, especially if they cannot explore online in the environment. These are critical …
policy data, especially if they cannot explore online in the environment. These are critical …
[HTML][HTML] Survey on evaluation methods for dialogue systems
In this paper, we survey the methods and concepts developed for the evaluation of dialogue
systems. Evaluation, in and of itself, is a crucial part during the development process. Often …
systems. Evaluation, in and of itself, is a crucial part during the development process. Often …
Graph-based, self-supervised program repair from diagnostic feedback
M Yasunaga, P Liang - International Conference on …, 2020 - proceedings.mlr.press
We consider the problem of learning to repair programs from diagnostic feedback (eg,
compiler error messages). Program repair is challenging for two reasons: First, it requires …
compiler error messages). Program repair is challenging for two reasons: First, it requires …