Large language models can learn temporal reasoning

S **ong, A Payani, R Kompella, F Fekri - arxiv preprint arxiv:2401.06853, 2024 - arxiv.org
While large language models (LLMs) have demonstrated remarkable reasoning capabilities,
they are not without their flaws and inaccuracies. Recent studies have introduced various …

Mt-bench-101: A fine-grained benchmark for evaluating large language models in multi-turn dialogues

G Bai, J Liu, X Bu, Y He, J Liu, Z Zhou, Z Lin… - arxiv preprint arxiv …, 2024 - arxiv.org
The advent of Large Language Models (LLMs) has drastically enhanced dialogue systems.
However, comprehensively evaluating the dialogue abilities of LLMs remains a challenge …

Jailbreakzoo: Survey, landscapes, and horizons in jailbreaking large language and vision-language models

H **, L Hu, X Li, P Zhang, C Chen, J Zhuang… - arxiv preprint arxiv …, 2024 - arxiv.org
The rapid evolution of artificial intelligence (AI) through developments in Large Language
Models (LLMs) and Vision-Language Models (VLMs) has brought significant advancements …

Model tailor: Mitigating catastrophic forgetting in multi-modal large language models

D Zhu, Z Sun, Z Li, T Shen, K Yan, S Ding… - arxiv preprint arxiv …, 2024 - arxiv.org
Catastrophic forgetting emerges as a critical challenge when fine-tuning multi-modal large
language models (MLLMs), where improving performance on unseen tasks often leads to a …

Insectmamba: Insect pest classification with state space model

Q Wang, C Wang, Z Lai, Y Zhou - arxiv preprint arxiv:2404.03611, 2024 - arxiv.org
The classification of insect pests is a critical task in agricultural technology, vital for ensuring
food security and environmental sustainability. However, the complexity of pest …

Mapo: Boosting large language model performance with model-adaptive prompt optimization

Y Chen, Z Wen, G Fan, Z Chen, W Wu, D Liu… - arxiv preprint arxiv …, 2024 - arxiv.org
Prompt engineering, as an efficient and effective way to leverage Large Language Models
(LLM), has drawn a lot of attention from the research community. The existing research …

Federated Learning for Smart Grid: A Survey on Applications and Potential Vulnerabilities

Z Zhang, S Rath, J Xu, T **ao - arxiv preprint arxiv:2409.10764, 2024 - arxiv.org
The Smart Grid (SG) is a critical energy infrastructure that collects real-time electricity usage
data to forecast future energy demands using information and communication technologies …

Optimizing search advertising strategies: Integrating reinforcement learning with generalized second-price auctions for enhanced ad ranking and bidding

C Zhou, Y Zhao, J Cao, Y Shen, X Cui… - … Algorithms and Signal …, 2024 - spiedigitallibrary.org
This paper explores the integration of strategic optimization methods in the context of search
advertising, focusing on ad ranking and bidding mechanisms within e-commerce platforms …

Research on driver facial fatigue detection based on Yolov8 model

C Zhou, Y Zhao, S Liu, Y Zhao, X Li… - 2024 5th International …, 2024 - ieeexplore.ieee.org
In a society where traffic accidents frequently occur, fatigue driving has emerged as a grave
issue. Fatigue driving detection technology, especially those based on the YOLOv8 deep …

Model extraction attacks revisited

J Liang, R Pang, C Li, T Wang - Proceedings of the 19th ACM Asia …, 2024 - dl.acm.org
Model extraction (ME) attacks represent one major threat to Machine-Learning-as-a-Service
(MLaaS) platforms by" stealing" the functionality of confidential machine-learning models …