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SCHRODINGER 'SMEMORY : LARGE LANGUAGE MOD-ELS Wei Wang Department of Computing The Hong Kong Polytechnic University weiuat. wang@connect. polyu. hk Qing Li Department of Computing The Hong Kong Polytechnic University qing-prof. li@polyu. edu. hk ABSTRACT Memory is the foundation of LLMs' functionality, yet past researc... | 2409.10482v1.pdf |
This paper will leverage the Universal Approximation Theorem (UAT) to explain the reasoning and memory abilities of LLMs. The contributions of this work are as follows: An explanation of LLMs' memory and reasoning abilities through the lens of UAT. A new, more objective method for evaluating LLMs' memory and reasoning ... | 2409.10482v1.pdf |
of multi-layer Transformers aligns with the UAT in a general sense. However, unlike the original UAT, the UAT form of Transformer-based models has the ability to dynamically fit functions based on the input. Figure 1 illustrates a basic Transformer module, and according to UAT2LLMs, the corresponding UAT form for Figur... | 2409.10482v1.pdf |
Memory is defined by two key components: input and output. Input: The input is information that is the same or similar to what the brain (or an LLM) has previously encountered (this is a necessary condition for memory—without input, there is no memory). Output: The result based on the input, which could be correct, inc... | 2409.10482v1.pdf |
of memory we provided. The training process is akin to giving a person 2,000 poems and asking them to memorize as many as possible, with a limit of reading each poem only 100 times. In the CN Poems dataset, the best-performing models were Qwen2-1. 5B-Instruct and bloom-1b4-zh, which remembered 1,938 and 1,932 poems res... | 2409.10482v1.pdf |
Model: Qwen1. 5-0. 5B-Chat Output: Let us build a fire In the living room Where living is done. The kitchen plants need Mowing and the cabinets To be axed and split into Kindling. W e'll slink inside Dresses, apply the brightest Rouge. Prettiest conflagration. Label: When the day closes, my grief's a laundromat done tu... | 2409.10482v1.pdf |
memory”—we can only determine if an LLM remembers something after posing a question and examining the output. Otherwise, it is impossible to know. Humans operate similarly: we can only verify our memory by answering specific questions; otherwise, we cannot assess it. For example, if you ask someone how many poems they ... | 2409.10482v1.pdf |
strong ability to adaptively fit inputs. As a result, LLMs can recall entire content based on minimal input information. Since this memory can only be confirmed when triggered by input, we refer to it as ”Schr ¨odinger's memory. ” Through extensive experiments, we validated that the memory mechanism of LLMs aligns with... | 2409.10482v1.pdf |
William Beecher Scoville and B. Milner. Loss of recent memory after bilateral hippocampal lesions. Journal of Neurology, Neurosurgery & Psychiatry, 20:11-21, 1957. URL https://api. semanticscholar. org/Corpus ID:20365179. Larry R. Squire. Memory and the hippocampus: a synthesis from findings with rats, mon-keys, and hu... | 2409.10482v1.pdf |
Miruna Clinciu, Najoung Kim, Newton Cheng, Oleg Serikov, Omer Antverg, Oskar van der Wal, Rui Zhang, Ruochen Zhang, Sebastian Gehrmann, Shachar Mirkin, Shani Pais, Tatiana Shav-rina, Thomas Scialom, Tian Yun, Tomasz Limisiewicz, Verena Rieser, Vitaly Protasov, Vladislav Mikhailov, Yada Pruksachatkun, Yonatan Belinkov, ... | 2409.10482v1.pdf |
Zhenyu (Allen) Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher R ´e, Clark W. Barrett, Zhangyang Wang, and Beidi Chen. H2o: Heavy-hitter oracle for efficient generative inference of large language mod-els. Ar Xiv, abs/2306. 14048, 2023. URL https://api. sem... | 2409.10482v1.pdf |
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