[PDF][PDF] A survey on large language models: Applications, challenges, limitations, and practical usage
Within the vast expanse of computerized language processing, a revolutionary entity known
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
[PDF][PDF] Large language models: a comprehensive survey of its applications, challenges, limitations, and future prospects
Within the vast expanse of computerized language processing, a revolutionary entity known
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
Parallelizing linear transformers with the delta rule over sequence length
Transformers with linear attention (ie, linear transformers) and state-space models have
recently been suggested as a viable linear-time alternative to transformers with softmax …
recently been suggested as a viable linear-time alternative to transformers with softmax …
Tptu: Task planning and tool usage of large language model-based ai agents
With recent advancements in natural language processing, Large Language Models (LLMs)
have emerged as powerful tools for various real-world applications. Despite their prowess …
have emerged as powerful tools for various real-world applications. Despite their prowess …
Simple linear attention language models balance the recall-throughput tradeoff
Recent work has shown that attention-based language models excel at recall, the ability to
ground generations in tokens previously seen in context. However, the efficiency of attention …
ground generations in tokens previously seen in context. However, the efficiency of attention …
Lotus: Enabling semantic queries with llms over tables of unstructured and structured data
The semantic capabilities of language models (LMs) have the potential to enable rich
analytics and reasoning over vast knowledge corpora. Unfortunately, existing systems lack …
analytics and reasoning over vast knowledge corpora. Unfortunately, existing systems lack …
[HTML][HTML] To prompt or not to prompt: Navigating the use of large language models for integrating and modeling heterogeneous data
Manually integrating data of diverse formats and languages is vital to many artificial
intelligence applications. However, the task itself remains challenging and time-consuming …
intelligence applications. However, the task itself remains challenging and time-consuming …
CHORUS: foundation models for unified data discovery and exploration
We apply foundation models to data discovery and exploration tasks. Foundation models
include large language models (LLMs) that show promising performance on a range of …
include large language models (LLMs) that show promising performance on a range of …
Embedding-based retrieval with llm for effective agriculture information extracting from unstructured data
Pest identification is a crucial aspect of pest control in agriculture. However, most farmers
are not capable of accurately identifying pests in the field, and there is a limited number of …
are not capable of accurately identifying pests in the field, and there is a limited number of …
From BERT to GPT-3 codex: harnessing the potential of very large language models for data management
I Trummer - arxiv preprint arxiv:2306.09339, 2023 - arxiv.org
Large language models have recently advanced the state of the art on many natural
language processing benchmarks. The newest generation of models can be applied to a …
language processing benchmarks. The newest generation of models can be applied to a …