Results 11 to 20 of about 544,328 (310)
Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic [PDF]
arXiv.org, 2023 In human conversations, individuals can indicate relevant regions within a scene while addressing others. In turn, the other person can then respond by referring to specific regions if necessary.
Ke Chen +5 more
semanticscholar +1 more source
MultiModal-GPT: A Vision and Language Model for Dialogue with Humans [PDF]
arXiv.org, 2023 We present a vision and language model named MultiModal-GPT to conduct multi-round dialogue with humans. MultiModal-GPT can follow various instructions from humans, such as generating a detailed caption, counting the number of interested objects, and ...
T. Gong +9 more
semanticscholar +1 more source
Zhongjing: Enhancing the Chinese Medical Capabilities of Large Language Model through Expert Feedback and Real-world Multi-turn Dialogue [PDF]
AAAI Conference on Artificial Intelligence, 2023 Recent advances in Large Language Models (LLMs) have achieved remarkable breakthroughs in understanding and responding to user intents. However, their performance lag behind general use cases in some expertise domains, such as Chinese medicine.
Songhua Yang +6 more
semanticscholar +1 more source
Improving alignment of dialogue agents via targeted human judgements [PDF]
arXiv.org, 2022 We present Sparrow, an information-seeking dialogue agent trained to be more helpful, correct, and harmless compared to prompted language model baselines.
Amelia Glaese +33 more
semanticscholar +1 more source
Internet-Augmented Dialogue Generation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2021 The largest store of continually updating knowledge on our planet can be accessed via internet search. In this work we study giving access to this information to conversational agents. Large language models, even though they store an impressive amount of
M. Komeili, Kurt Shuster, J. Weston
semanticscholar +1 more source
DialogSum: A Real-Life Scenario Dialogue Summarization Dataset [PDF]
Findings, 2021 Proposal of large-scale datasets has facilitated research on deep neural models for news summarization. Deep learning can also be potentially useful for spoken dialogue summarization, which can benefit a range of real-life scenarios including customer ...
Yulong Chen +3 more
semanticscholar +1 more source
Personalizing Dialogue Agents: I have a dog, do you have pets too? [PDF]
Annual Meeting of the Association for Computational Linguistics, 2018 Chit-chat models are known to have several problems: they lack specificity, do not display a consistent personality and are often not very captivating.
Saizheng Zhang +5 more
semanticscholar +1 more source
MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling [PDF]
Conference on Empirical Methods in Natural Language Processing, 2018 Even though machine learning has become the major scene in dialogue research community, the real breakthrough has been blocked by the scale of data available.To address this fundamental obstacle, we introduce the Multi-Domain Wizard-of-Oz dataset ...
Paweł Budzianowski +6 more
semanticscholar +1 more source
Is ChatGPT Equipped with Emotional Dialogue Capabilities? [PDF]
arXiv.org, 2023 This report presents a study on the emotional dialogue capability of ChatGPT, an advanced language model developed by OpenAI. The study evaluates the performance of ChatGPT on emotional dialogue understanding and generation through a series of ...
Weixiang Zhao +5 more
semanticscholar +1 more source
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System [PDF]
Annual Meeting of the Association for Computational Linguistics, 2021 Pre-trained language models have been recently shown to benefit task-oriented dialogue (TOD) systems. Despite their success, existing methods often formulate this task as a cascaded generation problem which can lead to error accumulation across different
Yixuan Su +6 more
semanticscholar +1 more source