27 papers · ranked by Valyu relevance
Roman Linne, Jannis Hildebrandt, Gerd Bohner, Hans-Peter Erb
We present a theory of sequential information processing in persuasion (SIP). It extends assumptions of the heuristic-systematic model, in particular the idea that information encountered early in a persuasion situation may affect the processing of subsequent information. SIP also builds on the abstraction from…
Lynn K. A. Sörensen, Sander M. Bohté, Dorina de Jong, Heleen A. Slagter + 1 more
Humans can rapidly recognize objects in a dynamically changing world. This ability is showcased by the fact that observers succeed at recognizing objects in rapidly changing image sequences, at up to 13 ms/image. To date, the mechanisms that govern dynamic object recognition remain poorly understood. Here, we developed…
Tomoya Nakai, Tatsuya Daikoku, Yohei Oseki
Humans use various sequential signals, such as language, music, and mathematics, to convey complex information and facilitate communication. Previous research has identified two fundamental frameworks underlying human sequential signal processing: a structural framework, emphasizing rule-based hierarchical organization…
Lennard J. Kwakernaak, Martin van Hecke
Materials with an irreversible response to cyclic driving exhibit an evolving internal state which, in principle, encodes information on the driving history. Here we realize irreversible metamaterials that count mechanical driving cycles and store the result into easily interpretable internal states. We extend these…
Kevin Zhang, Neha Patki, Kalyan Veeramachaneni
The goal of this paper is to describe a system for generating synthetic sequential data within the Synthetic data vault. To achieve this, we present the Sequential model currently in SDV, an end-to-end framework that builds a generative model for multi-sequence, real-world data. This includes a novel neural…
Bing Han, Cheng Wang, Kaushik Roy
Tremendous progress has been made in sequential processing with the recent advances in recurrent neural networks. However, recurrent architectures face the challenge of exploding/vanishing gradients during training, and require significant computational resources to execute back-propagation through time. Moreover…
Lynn K. A. Sörensen, Sander M. Bohté, Dorina de Jong, Heleen A. Slagter + 2 more
'Heleen A. Slagter' 'H. Steven Scholte' 'Matthieu Louis'] Humans can quickly recognize objects in a dynamically changing world. This ability is showcased by the fact that observers succeed at recognizing objects in rapidly changing image sequences, at up to 13 ms/image. To date, the mechanisms that govern dynamic…
Si Cheng, Siyi Chen, Zhuanghua Shi
Our current perception and decision-making are shaped by recent experiences, a phenomenon known as serial dependence. While serial dependence is well-documented in visual perception and has been recently explored in time perception, their functional similarities across non-temporal and temporal domains remain elusive…
Vida Ranjbar, Robbert Beerten, Marc Moonen, Sofie Pollin
—Cell-free massive multiple-input multiple-output (MIMO) is an emerging technology that will reshape the architecture of next-generation networks. This paper considers the sequential fronthaul, whereby the access points (APs) are connected in a daisy chain topology with multiple sequential processing stages. With this…
Daniel Waxman, Fernando Llorente, Petar M. Djurić
The proliferation of capable and efficient machine learning (ML) models marks one of the strongest methodological shifts in signal processing (SP) in its nearly 100-year history. ML models support the development of SP systems that represent complex, nonlinear relationships with high predictive accuracy. Adapting these…
Lei Deng, Lei Chen, Jingjie Zhao, Ruimei Wang + 1 more
Short response time for order processing is important for modern warehouses, which can be potentially achieved by adopting appropriate processing policy. The parallel processing policy have advantages in improving performance of many autonomous storage and retrieval systems. However, researchers tend to assume a…
Willem B. Verwey
An exhaustive review is reported of over 25 years of research with the Discrete Sequence Production (DSP) task as reported in well over 100 articles. In line with the increasing call for theory development, this culminates into proposing the second version of the Cognitive framework of Sequential Motor Behavior (C-SMB…
Andrew D Levy, Peter Zeidman, Karl Friston
Sequential experimental paradigms are fundamental to cognitive neuroscience, yet standard event-related response analysis struggles with the temporal variability inherent to these designs. Conventional epoching treats each event within a sequence as an independent response, discarding the temporal dependencies between…
Michele Fornaciai, Irene Togoli, Samuel Binisti, Olivier Collignon
Our perception often shows systematic biases revealing how the brain’s internal representation diverges from the physical world. In particular, what happened in the recent past can systematically attract current percepts, making them appear more similar to previous stimuli. Does this phenomenon reflect a low-level…
Jon Sporring, David Stansby
This report addresses larger-than-memory image analysis for petascale datasets such as 1.4 PB electron-microscopy volumes [[4]] and 150 TB human-organ atlases [[6]]. We argue that performance is fundamentally I/O-bound rather than compute-bound. We show that structuring analysis as streaming passes over data is…
Leonardo Bonetti, Gemma Fernández-Rubio, Mattia Rosso, Francesco Carlomagno + 4 more
Predictive coding posits that the brain continuously generates and updates internal models to anticipate incoming sensory input. While auditory and visual modalities have been studied independently in this context, direct comparisons using matched paradigms are scarce. Here, we employed magnetoencephalography (MEG) to…
Marta Szewczyk, Paweł Augustynowicz, Magdalena Szubielska
Introduction While most studies on implicit sequential learning focus on object learning, the hidden structure of target location and onset time can also be a subject of implicitly gathered knowledge. In our study, we wanted to investigate the effect of implicitly learned spatial and temporal sequential predictability…
Marius Barth, Christoph Stahl, Hilde Haider
Sequence learning in the serial response time task (SRTT) is one of few learning phenomena where researchers agree that such learning may proceed in the absence of awareness, while it is also possible to explicitly learn a sequence of events. In the past few decades, research into sequence learning largely focused on…
Ao Sun, Weilin Zhao, Xu Han, Cheng Yang + 3 more
Language Model Training Authors: ['Ao Sun' 'Weilin Zhao' 'Xu Han' 'Cheng Yang' 'Zhiyuan Liu' 'Chuan Shi' 'Maosong Sun'] The emergence of large language models (LLMs) relies heavily on distributed training strategies, among which pipeline parallelism plays a crucial role. As LLMs' training sequence length extends to 32k…
Michael William Simpson, Jing Wu, Zheng Ye
Sequence specific learning was observed under both neutral and congruent prime conditions (Fig. [Fig2], [Fig2], Fig. [Fig3], [Fig3]), yet the magnitude was significantly greater with congruent primes, suggesting that in addition to baseline congruency effects, prime congruency may also mediate implicit learning.…
Xiongbo Wu, Lluís Fuentemilla
In episodic encoding, an unfolding experience is rapidly transformed into a memory representation that binds separate episodic elements into a memory form to be later recollected. However, it is unclear how brain activity changes over time to accommodate the encoding of incoming information. This study aimed to…
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This research presents a novel approach to obstacle detection during navigation using a combination of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The primary objective is to generate accurate image captions that describe the content of images, which is crucial for applications such…
Aaron Liu, Myeongyeon Lee, Rahul Venkatesh, Jessica Bonsu + 4 more
Polymer-based semiconductors and organic electronics encapsulate a significant research thrust for informatics-driven materials development. However, device measurements are described by a complex array of design and parameter choices, many of which are sparsely reported. For example, the mobility of a polymer-based…
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Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…
Chenxi Sui, Ziyang Jiang, Genesis Higueros, David Carlson + 1 more
High-performance batteries are poised for electrification of vehicles and therefore mitigate greenhouse gas emissions, which, in turn, promote a sustainable future. However, the design of optimized batteries is challenging due to the nonlinear governing physics and electrochemistry. Recent advancements have…
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Background: Pharmaceutical batch production faces significant scheduling challenges due to operational uncertainties including equipment failures, yield variability, and demand fluctuations. While scheduling heuristics are widely used in practice, their comparative performance under varying uncertainty conditions…
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Automated chemistry platforms hold the potential to enable large-scale organic synthesis campaigns, such as producing a library of compounds for biological evaluation. The efficiency of such platforms will depend on the schedule according to which the synthesis operations are executed. In this work, we study the…