Unifying large language models and knowledge graphs: A roadmap

S Pan, L Luo, Y Wang, C Chen… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …

Netllm: Adapting large language models for networking

D Wu, X Wang, Y Qiao, Z Wang, J Jiang, S Cui… - Proceedings of the …, 2024‏ - dl.acm.org
Many networking tasks now employ deep learning (DL) to solve complex prediction and
optimization problems. However, current design philosophy of DL-based algorithms entails …

Interactive natural language processing

Z Wang, G Zhang, K Yang, N Shi, W Zhou… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Interactive Natural Language Processing (iNLP) has emerged as a novel paradigm within
the field of NLP, aimed at addressing limitations in existing frameworks while aligning with …

Beyond efficiency: A systematic survey of resource-efficient large language models

G Bai, Z Chai, C Ling, S Wang, J Lu, N Zhang… - arxiv preprint arxiv …, 2024‏ - arxiv.org
The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated
models like OpenAI's ChatGPT, represents a significant advancement in artificial …

Doraemongpt: Toward understanding dynamic scenes with large language models

Z Yang, G Chen, X Li, W Wang, Y Yang - arxiv preprint arxiv:2401.08392, 2024‏ - arxiv.org
The field of AI agents is advancing at an unprecedented rate due to the capabilities of large
language models (LLMs). However, LLM-driven visual agents mainly focus on solving tasks …

Dehallucinating large language models using formal methods guided iterative prompting

S Jha, SK Jha, P Lincoln, ND Bastian… - 2023 IEEE …, 2023‏ - ieeexplore.ieee.org
Large language models (LLMs) such as ChatGPT have been trained to generate human-like
responses to natural language prompts. LLMs use a vast corpus of text data for training, and …

Creating trustworthy llms: Dealing with hallucinations in healthcare ai

MA Ahmad, I Yaramis, TD Roy - arxiv preprint arxiv:2311.01463, 2023‏ - arxiv.org
Large language models have proliferated across multiple domains in as short period of time.
There is however hesitation in the medical and healthcare domain towards their adoption …

Chatdb: Augmenting llms with databases as their symbolic memory

C Hu, J Fu, C Du, S Luo, J Zhao, H Zhao - arxiv preprint arxiv:2306.03901, 2023‏ - arxiv.org
Large language models (LLMs) with memory are computationally universal. However,
mainstream LLMs are not taking full advantage of memory, and the designs are heavily …

Fourier transformer: Fast long range modeling by removing sequence redundancy with fft operator

Z He, M Yang, M Feng, J Yin, X Wang, J Leng… - arxiv preprint arxiv …, 2023‏ - arxiv.org
The transformer model is known to be computationally demanding, and prohibitively costly
for long sequences, as the self-attention module uses a quadratic time and space complexity …

The effect of scaling, retrieval augmentation and form on the factual consistency of language models

L Hagström, D Saynova, T Norlund… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Large Language Models (LLMs) make natural interfaces to factual knowledge, but their
usefulness is limited by their tendency to deliver inconsistent answers to semantically …