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Large language models can learn temporal reasoning
While large language models (LLMs) have demonstrated remarkable reasoning capabilities,
they are not without their flaws and inaccuracies. Recent studies have introduced various …
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
The advent of Large Language Models (LLMs) has drastically enhanced dialogue systems.
However, comprehensively evaluating the dialogue abilities of LLMs remains a challenge …
However, comprehensively evaluating the dialogue abilities of LLMs remains a challenge …
Jailbreakzoo: Survey, landscapes, and horizons in jailbreaking large language and vision-language models
The rapid evolution of artificial intelligence (AI) through developments in Large Language
Models (LLMs) and Vision-Language Models (VLMs) has brought significant advancements …
Models (LLMs) and Vision-Language Models (VLMs) has brought significant advancements …
Model tailor: Mitigating catastrophic forgetting in multi-modal large language models
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 …
language models (MLLMs), where improving performance on unseen tasks often leads to a …
Insectmamba: Insect pest classification with state space model
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 …
food security and environmental sustainability. However, the complexity of pest …
Mapo: Boosting large language model performance with model-adaptive prompt optimization
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 …
(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
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 …
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
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 …
advertising, focusing on ad ranking and bidding mechanisms within e-commerce platforms …
Research on driver facial fatigue detection based on Yolov8 model
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 …
issue. Fatigue driving detection technology, especially those based on the YOLOv8 deep …
Model extraction attacks revisited
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 …
(MLaaS) platforms by" stealing" the functionality of confidential machine-learning models …