15 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…
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…
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…
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…
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.…