Retrieval-augmented generation for large language models: A survey

Y Gao, Y **ong, X Gao, K Jia, J Pan, Y Bi, Y Dai… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models (LLMs) demonstrate powerful capabilities, but they still face
challenges in practical applications, such as hallucinations, slow knowledge updates, and …

Security and privacy challenges of large language models: A survey

BC Das, MH Amini, Y Wu - ACM Computing Surveys, 2024 - dl.acm.org
Large language models (LLMs) have demonstrated extraordinary capabilities and
contributed to multiple fields, such as generating and summarizing text, language …

Recommendation as instruction following: A large language model empowered recommendation approach

J Zhang, R **e, Y Hou, X Zhao, L Lin… - ACM Transactions on …, 2023 - dl.acm.org
In the past decades, recommender systems have attracted much attention in both research
and industry communities. Existing recommendation models mainly learn the underlying …

Towards open-world recommendation with knowledge augmentation from large language models

Y **, W Liu, J Lin, X Cai, H Zhu, J Zhu, B Chen… - Proceedings of the 18th …, 2024 - dl.acm.org
Recommender system plays a vital role in various online services. However, its insulated
nature of training and deploying separately within a specific closed domain limits its access …

Large language models are effective text rankers with pairwise ranking prompting

Z Qin, R Jagerman, K Hui, H Zhuang, J Wu… - arxiv preprint arxiv …, 2023 - arxiv.org
Ranking documents using Large Language Models (LLMs) by directly feeding the query and
candidate documents into the prompt is an interesting and practical problem. However …

Dense text retrieval based on pretrained language models: A survey

WX Zhao, J Liu, R Ren, JR Wen - ACM Transactions on Information …, 2024 - dl.acm.org
Text retrieval is a long-standing research topic on information seeking, where a system is
required to return relevant information resources to user's queries in natural language. From …

How can recommender systems benefit from large language models: A survey

J Lin, X Dai, Y **, W Liu, B Chen, H Zhang… - ACM Transactions on …, 2023 - dl.acm.org
With the rapid development of online services and web applications, recommender systems
(RS) have become increasingly indispensable for mitigating information overload and …

Don't make your llm an evaluation benchmark cheater

K Zhou, Y Zhu, Z Chen, W Chen, WX Zhao… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models~(LLMs) have greatly advanced the frontiers of artificial intelligence,
attaining remarkable improvement in model capacity. To assess the model performance, a …

Llm for soc security: A paradigm shift

D Saha, S Tarek, K Yahyaei, SK Saha, J Zhou… - IEEE …, 2024 - ieeexplore.ieee.org
As the ubiquity and complexity of system-on-chip (SoC) designs increase across electronic
devices, incorporating security into an SoC design flow poses significant challenges …

Grounding and evaluation for large language models: Practical challenges and lessons learned (survey)

K Kenthapadi, M Sameki, A Taly - Proceedings of the 30th ACM SIGKDD …, 2024 - dl.acm.org
With the ongoing rapid adoption of Artificial Intelligence (AI)-based systems in high-stakes
domains, ensuring the trustworthiness, safety, and observability of these systems has …