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In this paper, we focus on the personalized response generation for conversational systems. Based on the sequence to sequence learning, especially the encoder-decoder framework, we propose a two-phase approach, namely initialization then…

Computation and Language · Computer Science 2019-12-03 Weinan Zhang , Ting Liu , Yifa Wang , Qingfu Zhu

The rapid evolution of Large Language Models (LLM) and subsequent Agentic AI technologies requires systematic architectural guidance for building sophisticated, production-grade systems. This paper presents an approach for architecting such…

Artificial Intelligence · Computer Science 2026-05-26 Zoran Milosevic , Fethi Rabhi

In recent years generative design techniques have become firmly established in numerous applied fields, especially in engineering. These methods are demonstrating intensive growth owing to promising outlook. However, existing approaches are…

Neural and Evolutionary Computing · Computer Science 2022-12-29 Nikita O. Starodubcev , Nikolay O. Nikitin , Konstantin G. Gavaza , Elizaveta A. Andronova , Denis O. Sidorenko , Anna V. Kalyuzhnaya

Actual organizations, in particular the ones which operate in evolving and distributed environments, need advanced frameworks for the management of the knowledge life cycle. These systems have to be based on the social relations which…

General Physics · Physics 2010-04-26 Luigi Lella , Ignazio Licata

We introduce a globally normalized transition-based neural network model that achieves state-of-the-art part-of-speech tagging, dependency parsing and sentence compression results. Our model is a simple feed-forward neural network that…

Computation and Language · Computer Science 2016-06-09 Daniel Andor , Chris Alberti , David Weiss , Aliaksei Severyn , Alessandro Presta , Kuzman Ganchev , Slav Petrov , Michael Collins

Designing adaptive mechanisms to align individual and collective interests remains a central challenge in artificial social intelligence. Existing methods often struggle with modeling heterogeneous agents possessing persistent latent traits…

Computers and Society · Computer Science 2025-10-23 Xiaoyuan Zhang , Yizhe Huang , Chengdong Ma , Zhixun Chen , Long Ma , Yali Du , Song-Chun Zhu , Yaodong Yang , Xue Feng

Generative adversarial networks achieve great performance in photorealistic image synthesis in various domains, including human images. However, they usually employ latent vectors that encode the sampled outputs globally. This does not…

Computer Vision and Pattern Recognition · Computer Science 2021-03-15 Kripasindhu Sarkar , Lingjie Liu , Vladislav Golyanik , Christian Theobalt

We investigate mechanisms for language change within a framework where an unconventional signal for a meaning is first innovated, and then subsequently propagated through a speech community to replace the existing convention. We appeal to…

Physics and Society · Physics 2015-08-24 Richard A Blythe

A critical factor in the success of decision support systems is the accurate modeling of user preferences. Psychology research has demonstrated that users often develop their preferences during the elicitation process, highlighting the…

Human-Computer Interaction · Computer Science 2024-10-03 Connor Lawless , Jakob Schoeffer , Lindy Le , Kael Rowan , Shilad Sen , Cristina St. Hill , Jina Suh , Bahareh Sarrafzadeh

Developing a universal model that can effectively harness heterogeneous resources and respond to a wide range of personalized needs has been a longstanding community aspiration. Our daily choices, especially in domains like fashion and…

Information Retrieval · Computer Science 2024-03-29 Tianxin Wei , Bowen Jin , Ruirui Li , Hansi Zeng , Zhengyang Wang , Jianhui Sun , Qingyu Yin , Hanqing Lu , Suhang Wang , Jingrui He , Xianfeng Tang

In recent years several novel models were developed to process natural language, development of accurate language translation systems have helped us overcome geographical barriers and communicate ideas effectively. These models are…

Computation and Language · Computer Science 2019-02-19 Sangarshanan Veeraraghavan

A generative recurrent neural network is quickly trained in an unsupervised manner to model popular reinforcement learning environments through compressed spatio-temporal representations. The world model's extracted features are fed into…

Machine Learning · Computer Science 2018-09-07 David Ha , Jürgen Schmidhuber

World Models have emerged as a powerful paradigm for learning compact, predictive representations of environment dynamics, enabling agents to reason, plan, and generalize beyond direct experience. Despite recent interest in World Models,…

Artificial Intelligence · Computer Science 2026-02-18 Lucas Maes , Quentin Le Lidec , Dan Haramati , Nassim Massaudi , Damien Scieur , Yann LeCun , Randall Balestriero

Trajectory data mining is crucial for smart city management. However, collecting large-scale trajectory datasets is challenging due to factors such as commercial conflicts and privacy regulations. Therefore, we urgently need trajectory…

Machine Learning · Computer Science 2025-02-04 Jingyuan Wang , Yujing Lin , Yudong Li

Foundation model-enabled generative artificial intelligence facilitates the development and implementation of agents, which can leverage distinguished reasoning and language processing capabilities to takes a proactive, autonomous role to…

Artificial Intelligence · Computer Science 2024-11-07 Yue Liu , Sin Kit Lo , Qinghua Lu , Liming Zhu , Dehai Zhao , Xiwei Xu , Stefan Harrer , Jon Whittle

In this paper we provide a first analysis of the research questions that arise when dealing with the problem of communicating pieces of formal argumentation through natural language interfaces. It is a generally held opinion that formal…

Artificial Intelligence · Computer Science 2017-06-14 Federico Cerutti , Alice Toniolo , Timothy J. Norman

We develop a qualitative model of decision making with two aims: to describe how people make simple decisions and to enable computer programs to do the same. Current approaches based on Planning or Decisions Theory either ignore uncertainty…

Artificial Intelligence · Computer Science 2013-02-18 Blai Bonet , Hector Geffner

World building forms the foundation of any task that requires narrative intelligence. In this work, we focus on procedurally generating interactive fiction worlds---text-based worlds that players "see" and "talk to" using natural language.…

Artificial Intelligence · Computer Science 2020-01-29 Prithviraj Ammanabrolu , Wesley Cheung , Dan Tu , William Broniec , Mark O. Riedl

In this article, we present a fresh perspective on language, combining ideas from various sources, but mixed in a new synthesis. As in the minimalist program, the question is whether we can formulate an elegant formalism, a universal…

Computation and Language · Computer Science 2023-03-10 Loe Feijs

The process of revitalizing cities in the United States suffers from balky and unresponsive processes---de jure egalitarian but de facto controlled and mediated by city officials and powerful interests, not residents. We argue that,…

Human-Computer Interaction · Computer Science 2020-10-07 Sarah Cooney , Barath Raghavan