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We describe a class of tasks called decision-oriented dialogues, in which AI assistants such as large language models (LMs) must collaborate with one or more humans via natural language to help them make complex decisions. We formalize…

Computation and Language · Computer Science 2024-05-07 Jessy Lin , Nicholas Tomlin , Jacob Andreas , Jason Eisner

Although the Transformer translation model (Vaswani et al., 2017) has achieved state-of-the-art performance in a variety of translation tasks, how to use document-level context to deal with discourse phenomena problematic for Transformer…

Computation and Language · Computer Science 2018-10-09 Jiacheng Zhang , Huanbo Luan , Maosong Sun , FeiFei Zhai , Jingfang Xu , Min Zhang , Yang Liu

With the evolution of pre-trained language models, current open-domain dialogue systems have achieved great progress in conducting one-session conversations. In contrast, Multi-Session Conversation (MSC), which consists of multiple sessions…

Computation and Language · Computer Science 2023-02-03 Tong Zhang , Yong Liu , Boyang Li , Zhiwei Zeng , Pengwei Wang , Yuan You , Chunyan Miao , Lizhen Cui

In conversational search systems, a key component is to determine and clarify the intent behind complex queries. We view intent clarification in light of the exploratory search paradigm, where users, through an iterative, evolving process…

Information Retrieval · Computer Science 2026-03-09 Maik Larooij

This paper describes a compact and effective model for low-latency passage retrieval in conversational search based on learned dense representations. Prior to our work, the state-of-the-art approach uses a multi-stage pipeline comprising…

Information Retrieval · Computer Science 2021-11-30 Sheng-Chieh Lin , Jheng-Hong Yang , Jimmy Lin

Transformer-based models have transformed the landscape of natural language processing (NLP) and are increasingly applied to computer vision tasks with remarkable success. These models, renowned for their ability to capture long-range…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Gracile Astlin Pereira , Muhammad Hussain

Training machines to understand natural language and interact with humans is one of the major goals of artificial intelligence. Recent years have witnessed an evolution from matching networks to pre-trained language models (PrLMs). In…

Computation and Language · Computer Science 2023-01-12 Zhuosheng Zhang , Hai Zhao , Longxiang Liu

Conversational grounding is a collaborative mechanism for establishing mutual knowledge among participants engaged in a dialogue. This experimental study analyzes information-seeking conversations to investigate the capabilities of large…

Computation and Language · Computer Science 2024-06-05 Kristiina Jokinen , Phillip Schneider , Taiga Mori

Finding the optimal set of cloud resources to deploy a given workload at minimal cost while meeting a defined service level agreement is an active area of research. Combining tens of parameters applicable across a large selection of…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-27 Michael Johnston , Burkhard Ringlein , Christoph Hagleitner , Alessandro Pomponio , Vassilis Vassiliadis , Christian Pinto , Srikumar Venugopal

Software Development (SD) is remarkably dynamic and is critically dependent on the knowledge acquired by the project's software developers as the project progresses. Software developers need to understand large amounts of information…

Software Engineering · Computer Science 2023-05-02 Glaucia Melo , Luis Fernando Lins , Paulo Alencar , Donald Cowan

Task-oriented semantic parsing is a critical component of virtual assistants, which is responsible for understanding the user's intents (set reminder, play music, etc.). Recent advances in deep learning have enabled several approaches to…

Computation and Language · Computer Science 2020-10-08 Xilun Chen , Asish Ghoshal , Yashar Mehdad , Luke Zettlemoyer , Sonal Gupta

An extension of Transformers is proposed that enables explicit relational reasoning through a novel module called the Abstractor. At the core of the Abstractor is a variant of attention called relational cross-attention. The approach is…

Machine Learning · Statistics 2024-04-16 Awni Altabaa , Taylor Webb , Jonathan Cohen , John Lafferty

In multi-turn dialog, utterances do not always take the full form of sentences \cite{Carbonell1983DiscoursePA}, which naturally makes understanding the dialog context more difficult. However, it is essential to fully grasp the dialog…

Computation and Language · Computer Science 2020-12-15 Xiuying Chen , Zhi Cui , Jiayi Zhang , Chen Wei , Jianwei Cui , Bin Wang , Dongyan Zhao , Rui Yan

API search involves finding components in an API that are relevant to a programming task. For example, a programmer may need a function in a C library that opens a new network connection, then another function that sends data across that…

Software Engineering · Computer Science 2021-07-27 Zachary Eberhart , Collin McMillan

Generative encoder-decoder models offer great promise in developing domain-general dialog systems. However, they have mainly been applied to open-domain conversations. This paper presents a practical and novel framework for building…

Computation and Language · Computer Science 2017-06-27 Tiancheng Zhao , Allen Lu , Kyusong Lee , Maxine Eskenazi

Conversational interfaces are likely to become more efficient, intuitive and engaging way for human-computer interaction than today's text or touch-based interfaces. Current research efforts concerning conversational interfaces focus…

Human-Computer Interaction · Computer Science 2017-09-18 Svitlana Vakulenko , Ilya Markov , Maarten de Rijke

We study the problem of imposing conversational goals/keywords on open-domain conversational agents, where the agent is required to lead the conversation to a target keyword smoothly and fast. Solving this problem enables the application of…

Computation and Language · Computer Science 2021-03-02 Peixiang Zhong , Yong Liu , Hao Wang , Chunyan Miao

Sharing ideas through communication with peers is the primary mode of human interaction. Consequently, extensive research has been conducted in the area of conversational AI, leading to an increase in the availability and diversity of…

Computation and Language · Computer Science 2024-05-24 Shivani Kumar , Sumit Bhatia , Milan Aggarwal , Tanmoy Chakraborty

This paper discusses the potential for creating academic resources (tools, data, and evaluation approaches) to support research in conversational search, by focusing on realistic information needs and conversational interactions.…

The increasing reliance on digital information necessitates advancements in conversational search systems, particularly in terms of information transparency. While prior research in conversational information-seeking has concentrated on…

Information Retrieval · Computer Science 2024-05-07 Weronika Łajewska , Damiano Spina , Johanne Trippas , Krisztian Balog
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