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The rise and potential of large language model based agents: A survey
Z ** Transformer with Random-Access Reading for Long-Context Understanding
Long-context modeling presents a significant challenge for transformer-based large
language models (LLMs) due to the quadratic complexity of the self-attention mechanism …
language models (LLMs) due to the quadratic complexity of the self-attention mechanism …
Out-of-distribution generalisation in spoken language understanding
Test data is said to be out-of-distribution (OOD) when it unexpectedly differs from the training
data, a common challenge in real-world use cases of machine learning. Although OOD …
data, a common challenge in real-world use cases of machine learning. Although OOD …
[PDF][PDF] A comprehensive study on LLM agent challenges
This paper intricately examines the manifold challenges and inherent issues associated with
Large Language Models (LLMs), both for the models themselves and the human context. It …
Large Language Models (LLMs), both for the models themselves and the human context. It …
Length Generalization with Recursive Neural Networks and Beyond
JR Chowdhury - 2024 - search.proquest.com
Abstract We investigate Recursive Neural Networks (RvNNs) for language processing tasks.
Roughly, from a generalized perspective, RvNNs repeatedly apply some neural function on …
Roughly, from a generalized perspective, RvNNs repeatedly apply some neural function on …