24 papers · ranked by Valyu relevance
Xiaofang Yang, Lijun Li, Heng Zhou, Tong Zhu + 12 more
Recent years have witnessed increasing interest in extending large language models into agentic systems. While the effectiveness of agents has continued to improve, efficiency, which is crucial for real-world deployment, has often been overlooked. This paper therefore investigates efficiency from three core components…
Dylan J. Terstege, Isabella M. Durante, Jonathan R. Epp
Memory storage and retrieval are shaped by past experiences. Prior learning and memory episodes have numerous impacts on brain structure from micro to macroscale. Previous experience with specific forms of learning increases the efficiency of future learning. It is less clear whether such practice effects on one type…
Isabella C. Wagner, Boris N. Konrad, Philipp Schuster, Sarah Weisig + 8 more
Mnemonic techniques, such as the method of loci, can powerfully boost memory. Here, we compared memory athletes ranked among the world’s top 50 in memory sports to mnemonics-naïve controls. In a second study, participants completed a six-weeks memory training, working memory training, or no intervention. Behaviorally…
Hamish Nicholson, Periklis Chrysogelos, Anastasia Ailamaki
Analytical engines rely on in-memory data caching to avoid storage accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- and time-based caching decisions, however, are a proxy of the expected query execution speedup only when storage accesses are significantly…
Zane Z. Chou, Jean-Marie C. Bouteiller
Artificial neural networks are limited in the number of patterns that they can store and accurately recall, with capacity constraints arising from factors such as network size, architectural structure, pattern sparsity, and pattern dissimilarity. Exceeding these limits leads to recall errors, eventually leading to…
Onur Mutlu, Saugata Ghose, Juan Gómez-Luna, Rachata Ausavarungnirun
Today's systems are overwhelmingly designed to move data to computation. This design choice goes directly against at least three key trends in systems that cause performance, scalability and energy bottlenecks: (1) data access from memory is already a key bottleneck as applications become more data-intensive and memory…
Tobore Onojighofia Tobore
Understanding the mechanisms behind memory, learning, and behavior is crucial to human development and significant research has been done in this area. Classical and operant conditioning and other theories of learning have elucidated different mechanisms of learning and how it modulates behavior. Even with advances in…
Ho Ling Li, Mark C. W. van Rossum
Many aspects of the brain’s design can be understood as the result of evolutionary drive towards efficient use of metabolic energy. In addition to the energetic costs of neural computation and transmission, experimental evidence indicates that synaptic plasticity is metabolically demanding as well. As synaptic…
Jin Zhou, Hailu Yang, Steven Steven, Tang + 3 more
'Tongping Liu'] Fine-tuning with Reinforcement Learning with Human Feedback (RLHF) is essential for aligning large language models (LLMs). However, RLHF often encounters significant memory challenges. This study is the first to examine memory usage in the RLHF context, exploring various memory management strategies and…
Yong-Cheng Liaw, Shuo-Han Chen
—Owing to the huge success of generative artificial intelligence (AI), large language models (LLMs) have emerged as a core subclass, underpinning applications such as question answering, text generation, and code completion. While fine tuning these models on domain-specific data can yield significant performance gains…
Matthew L. Stanley, Sean L. Simpson, Dale Dagenbach, Robert G. Lyday + 3 more
'Jonathan H. Burdette' 'Paul J. Laurienti' 'Yong He'] Working memory is a complex psychological construct referring to the temporary storage and active processing of information. We used functional connectivity brain network metrics quantifying local and global efficiency of information transfer for predicting…
Michael J. Endres, Joseph W. Houpt, Chris Donkin, Peter R. Finn
Working memory capacity (WMC) is typically measured by the amount of task-relevant information an individual can keep in mind while resisting distraction or interference from task-irrelevant information. The current research investigated the extent to which differences in WMC were associated with performance on a novel…
Futing Zou, Sze Chai Kwok
Our subjective experience of remembering guides and monitors the reconstruction of past and simulation of the future, which enables us to identify mistakes and adjust our behavior accordingly. However, it remains incompletely understood what underlies the process of subjective mnemonic experience. Here, we combined…
Roselyne J. Chauvin, Annie Zheng, Athanasia Metoki, Samuel R. Krimmel + 19 more
Memory athletes can achieve superior performance (e.g., memorizing 339 digits in 5 minutes) with extensive daily training, by converting abstract information into vivid scenes, and placing them along a mental path, that is then retraced at recall (Method of Loci). Understanding the brain mechanisms underlying such…
Dhruv Mátáni, Gaurav Menghani
Applications making excessive use of single-object based data structures (such as linked lists, trees, etc...) can see a drop in efficiency over a period of time due to the randomization of nodes in memory. This slow down is due to the ineffective use of the CPU's L1/L2 cache. We present a novel approach for mitigating…
Deborah Talmi, Deimante Kavaliauskaite, Nathaniel D. Daw
When people encounter items that they believe will help them gain reward, they later remember them better than those that do not. While it is adaptive to preferentially remember experiences that will be useful later, it is unknown how the competition for memory resources is implemented in time, through the processes of…
Jeff Guo, Philippe Schwaller
Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy desired objectives under minimal oracle evaluations (computational prediction or wet-lab experiment). This problem becomes more apparent when using oracles that can provide increased…
Jeff Guo, Philippe Schwaller
Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy desired objectives under minimal oracle evaluations (computational prediction or wet-lab experiment). This problem becomes more apparent when using oracles that can provide increased…
Michał J. Wójcik, Amy Li, Dante Wasmuht, Jake P. Stroud + 3 more
Working memory has been traditionally studied as a passive storage for information. However, recent advances have suggested that working memory is prospective rather than retrospective, meaning that its content undergoes transformations that will support future behaviour. One perspective that underscores this notion…
Antonio Mastrogiorgio, Francesca Zaninotto, Francesca Maggi, Emiliano Ricciardi + 2 more
'Emiliano Ricciardi' 'Nicola Lattanzi' 'Andrea P. Malizia'] Enhancing cognitive memory through virtual reality represents an issue, that has never been investigated in organizational settings. Here, we compared a virtual memoryscape (treatment) - an immersive virtual environment used by subjects as a shared memory tool…
Authors not listed
This paper develops a comprehensive theoretical framework for designing quantum memory systems with enhanced resilience to thermal decoherence through engineered lattice geometries and protective structures. We formulate a unified mathematical description connecting material properties, geometric configurations, and…
Yingqi Tian, Zhaoxuan Xie, Zhen Luo, Haibo Ma
Using the mixed precision strategy to optimize quantum chemistry codes has been proved promising in saving computational cost and maintaining chemical accuracy. Here, an efficient mixed-precision density matrix renormalization group (DMRG) scheme, containing a two-level mixed-precision hierarchy, is developed and…
Authors not listed
A memristor is a two-terminal electronic component that modify its conductance state depending on how much charge has passed through it previously. Halide perovskites are materials recently employed for neuromorphic computing in this type of resistive switches. Their performance is rapidly improving, yet the activation…
Pierfrancesco Ombrini, Qidi Wang, Alexandros Vasileiadis, Fangting Wu + 6 more
Effective optimization and control of lithium-ion batteries cannot neglect the relation between fundamental physicochemical phenomena and performance. In this work, we apply a multi-step charging protocol to commercially relevant electrodes, such as LiNi0.8Mn0.1Co0.1O2 (NMC811), LiFePO4 (LFP), LiMn1.5Ni0.5O4 (LMNO)…