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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

The perceptual experience of architecture is enacted by the sensory and motor system. When we act, we change the perceived environment according to a set of expectations that depend on our body and the built environment. The continuous…

Neurons and Cognition · Quantitative Biology 2020-11-10 Zakaria Djebbara , Thomas Parr , Karl Friston

Textual explanations have proved to help improve user satisfaction on machine-made recommendations. However, current mainstream solutions loosely connect the learning of explanation with the learning of recommendation: for example, they are…

Information Retrieval · Computer Science 2021-01-26 Aobo Yang , Nan Wang , Hongbo Deng , Hongning Wang

Computer vision often treats human perception as homogeneous: an implicit assumption that visual stimuli are perceived similarly by everyone. This assumption is reflected in the way researchers collect datasets and train vision models. By…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Andre Ye , Sebastin Santy , Jena D. Hwang , Amy X. Zhang , Ranjay Krishna

We propose Perceptual Taxonomy, a structured process of scene understanding that first recognizes objects and their spatial configurations, then infers task-relevant properties such as material, affordance, function, and physical attributes…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Jonathan Lee , Xingrui Wang , Jiawei Peng , Luoxin Ye , Zehan Zheng , Tiezheng Zhang , Tao Wang , Wufei Ma , Siyi Chen , Yu-Cheng Chou , Prakhar Kaushik , Alan Yuille

Increasing diversity in language models is a challenging yet essential objective. A common approach is to raise the decoding temperature. In this work, we investigate this approach through a simplistic yet common case to provide insights…

Computation and Language · Computer Science 2025-08-14 Alexandre Verine , Florian Le Bronnec , Kunhao Zheng , Alexandre Allauzen , Yann Chevaleyre , Benjamin Negrevergne

Handling various objects with different colors is a significant challenge for image colorization techniques. Thus, for complex real-world scenes, the existing image colorization algorithms often fail to maintain color consistency. In this…

Computer Vision and Pattern Recognition · Computer Science 2023-04-26 Subhankar Ghosh , Saumik Bhattacharya , Prasun Roy , Umapada Pal , Michael Blumenstein

Inferring the abstract relational and causal structure of the world is a major challenge for reinforcement-learning (RL) agents. For humans, language--particularly in the form of explanations--plays a considerable role in overcoming this…

Humans have the ability to rapidly understand rich combinatorial concepts from limited data. Here we investigate this ability in the context of auditory signals, which have been evolved in a cultural transmission experiment to study the…

Computation and Language · Computer Science 2021-04-19 Matthias Hofer , Tuan Anh Le , Roger Levy , Josh Tenenbaum

Colour information not only helps sustain the survival of animal species by guiding sexual selection and foraging behaviour, but also is an important factor in the cultural and technological development of our own species. This is…

Neurons and Cognition · Quantitative Biology 2022-06-03 Birgitta Dresp-Langley , Adam Reeves

How do we imagine visual objects and combine them to create new forms? To answer this question, we need to explore the cognitive, computational and neural mechanisms underlying imagery and creativity. The body of research on deep learning…

Neurons and Cognition · Quantitative Biology 2021-12-14 Shekoofeh Hedayati , Roger Beaty , Brad Wyble

Human beings learn causal models and constantly use them to transfer knowledge between similar environments. We use this intuition to design a transfer-learning framework using object-oriented representations to learn the causal…

Machine Learning · Computer Science 2020-07-21 Purva Pruthi , Javier González , Xiaoyu Lu , Madalina Fiterau

How do learners acquire knowledge of what is unacceptable without negative evidence? Construction Grammar proposes statistical preemption: exposure to a conventional form (e.g., "donated the books to the library") preempts structurally…

Computation and Language · Computer Science 2026-05-25 Dongxin Guo , Jikun Wu , Siu Ming Yiu

Although an object may appear in numerous contexts, we often describe it in a limited number of ways. Language allows us to abstract away visual variation to represent and communicate concepts. Building on this intuition, we propose an…

Computer Vision and Pattern Recognition · Computer Science 2023-03-30 Mohamed El Banani , Karan Desai , Justin Johnson

Language decoding studies have identified word representations which can be used to predict brain activity in response to novel words and sentences (Anderson et al., 2016; Pereira et al., 2018). The unspoken assumption of these studies is…

Computation and Language · Computer Science 2018-06-05 Jon Gauthier , Anna Ivanova

A neural language model trained on a text corpus can be used to induce distributed representations of words, such that similar words end up with similar representations. If the corpus is multilingual, the same model can be used to learn…

Computation and Language · Computer Science 2019-01-10 Johannes Bjerva , Robert Östling , Maria Han Veiga , Jörg Tiedemann , Isabelle Augenstein

In the field of visual representation learning, performance of contrastive learning has been catching up with the supervised method which is commonly a classification convolutional neural network. However, most of the research work focuses…

Computer Vision and Pattern Recognition · Computer Science 2023-01-31 Xiaoqi Zhuang

The notions of concreteness and imageability, traditionally important in psycholinguistics, are gaining significance in semantic-oriented natural language processing tasks. In this paper we investigate the predictability of these two…

Computation and Language · Computer Science 2022-09-15 Nikola Ljubešić , Darja Fišer , Anita Peti-Stantić

Human color categories are not uniformly distributed in perceptual space, yet most computational color models still assume fixed and evenly structured representations. In this paper, we present a focused analytical extension of the COLIBRI…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Elnara Kadyrgali , Nuray Toganas , Muragul Muratbekova , Pakizar Shamoi

In English and other languages, multiple adjectives in noun phrases follow intricate ordering patterns. These patterns have been widely studied in linguistics and provide a useful test case for assessing how language models (LMs) acquire…

Computation and Language · Computer Science 2026-02-10 Jaap Jumelet , Lisa Bylinina , Willem Zuidema , Jakub Szymanik