5 citations · 7 across the 8 of their papers we have counts for
8 papers
MemEmo: Evaluating Emotion in Memory Systems of Agents
Peng Liu, Zhen Tao, Jihao Zhao +5
Memory systems address the challenge of context loss in Large Language Model during prolonged interactions. However, compared to human cognition, the efficacy of these systems in p…
LQRS: Learned Query Re-optimization Framework for Spark SQL
Jiahao He, Yutao Cui, Cuiping Li +3
The query optimizer is a fundamental component of database management systems. Recent studies have shown that learned query optimizers outperform traditional cost-based query optim…
Unsupervised Learning for Class Distribution Mismatch
Pan Du, Wangbo Zhao, Xinai Lu +8
Class distribution mismatch (CDM) refers to the discrepancy between class distributions in training data and target tasks. Previous methods address this by designing classifiers to…
LoRS: Efficient Low-Rank Adaptation for Sparse Large Language Model
Yuxuan Hu, Jing Zhang, Xiaodong Chen +3
Existing low-rank adaptation (LoRA) methods face challenges on sparse large language models (LLMs) due to the inability to maintain sparsity. Recent works introduced methods that m…
SAM Decoding: Speculative Decoding via Suffix Automaton
Yuxuan Hu, Ke Wang, Xiaokang Zhang +4
Speculative decoding (SD) has been demonstrated as an effective technique for lossless LLM inference acceleration. Retrieval-based SD methods, one kind of model-free method, have y…
Personalized Clustering via Targeted Representation Learning
Xiwen Geng, Suyun Zhao, Yixin Yu +5
Clustering traditionally aims to reveal a natural grouping structure within unlabeled data. However, this structure may not always align with users' preferences. In this paper, we…
Is Diffusion Model Safe? Severe Data Leakage via Gradient-Guided Diffusion Model
Jiayang Meng, Tao Huang, Hong Chen +1
Gradient leakage has been identified as a potential source of privacy breaches in modern image processing systems, where the adversary can completely reconstruct the training image…
FOSS: A Self-Learned Doctor for Query Optimizer
Kai Zhong, Luming Sun, Tao Ji +2
Various works have utilized deep learning to address the query optimization problem in database system. They either learn to construct plans from scratch in a bottom-up manner or s…