A survey on model compression for large language models

X Zhu, J Li, Y Liu, C Ma, W Wang - Transactions of the Association for …, 2024 - direct.mit.edu
Abstract Large Language Models (LLMs) have transformed natural language processing
tasks successfully. Yet, their large size and high computational needs pose challenges for …

Efficient evaluation methods for neural architecture search: A survey

X Song, X Xie, Z Lv, GG Yen, W Ding, J Lv… - arXiv preprint arXiv …, 2023 - arxiv.org
Neural Architecture Search (NAS) has received increasing attention because of its
exceptional merits in automating the design of Deep Neural Network (DNN) architectures …

Improving Differentiable Architecture Search via self-distillation

X Zhu, J Li, Y Liu, W Wang - Neural Networks, 2023 - Elsevier
Abstract Differentiable Architecture Search (DARTS) is a simple yet efficient Neural
Architecture Search (NAS) method. During the search stage, DARTS trains a supernet by …

Flexible order aware sequential recommendation

M Qian, X Gu, L Chu, F Dai, H Fan, B Li - Proceedings of the 2022 …, 2022 - dl.acm.org
Sequential recommendations can dynamically model user interests, which has great value
since users' interests may change rapidly with time. Traditional sequential recommendation …

IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate Importance

H He, L Liu, H Zhang, N Zheng - … of the AAAI Conference on Artificial …, 2024 - ojs.aaai.org
Among existing Neural Architecture Search methods, DARTS is known for its efficiency and
simplicity. This approach applies continuous relaxation of network representation to …

Robust Neural Architecture Search

X Zhu, J Li, Y Liu, W Wang - arXiv preprint arXiv:2304.02845, 2023 - arxiv.org
Neural Architectures Search (NAS) becomes more and more popular over these years.
However, NAS-generated models tends to suffer greater vulnerability to various malicious …

User Popularity Preference Aware Sequential Recommendation

M Qian, F Dai, X Gu, H Fan, D Liu, B Li - International Conference on …, 2023 - Springer
In recommender systems, users' preferences for item popularity are diverse and dynamic,
which reveals the different items that users prefer. Therefore, identifying user popularity …