Many recent advances in natural language generation have been fueled by training large language models on internet-scale data. However, this paradigm can lead to models that generate toxic, inaccurate, and unhelpful content, and automatic evaluation metrics often fail to identify these behaviors. As models become more capable, human feedback is an invaluable signal for evaluating… Continue reading Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation
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Representation Learning for Natural Language Processing
Provides a comprehensive overview of the representation learning techniques for natural language processing. Presents a systematic and thorough introduction to the theory, algorithms and applications of representation learning. Shares insights into the future research directions for each topic as well as for the overall field of representation learning for natural language processing.
From Statistical Methods to Deep Learning, Automatic Keyphrase Prediction: A Survey
Keyphrase prediction aims to generate phrases (keyphrases) that highly summarizes a given document. Recently, researchers have conducted in-depth studies on this task from various perspectives. In this paper, we comprehensively summarize representative studies from the perspectives of dominant models, datasets and evaluation metrics. Our work analyzes up to 167 previous works, achieving greater coverage of… Continue reading From Statistical Methods to Deep Learning, Automatic Keyphrase Prediction: A Survey
A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospects
Proactive dialogue systems, related to a wide range of real-world conversational applications, equip the conversational agent with the capability of leading the conversation direction towards achieving pre-defined targets or fulfilling certain goals from the system side. It is empowered by advanced techniques to progress to more complicated tasks that require strategical and motivational interactions. In… Continue reading A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospects
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition. The latest model developed by OpenAI, GPT-4, was trained using an unprecedented scale of compute and data. In this paper, we report on our… Continue reading Sparks of Artificial General Intelligence: Early experiments with GPT-4
A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT
Recently, ChatGPT, along with DALL-E-2 and Codex,has been gaining significant attention from society. As a result, many individuals have become interested in related resources and are seeking to uncover the background and secrets behind its impressive performance. In fact, ChatGPT and other Generative AI (GAI) techniques belong to the category of Artificial Intelligence Generated Content… Continue reading A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT