335 citations · 344 across the 10 of their papers we have counts for
10 papers
LoCA: Forward-Only LLM Tuning after One-Shot Calibration with Local Credit Assignment
Linhan Xia, Rui Liu, Zhaofeng Zhang +3
Parameter-efficient post-training reduces the number of trainable parameters, but still requires repeated end-to-end backpropagation through the frozen backbone. Every adaptation s…
Evolving in the Agent Jungle via History-Informed Opponent Awareness
Zhaofeng Zhang, Linhan Xia, Rui Liu +3
Learning to adapt strategies through interaction is a key step toward more general and autonomous LLM agents. Existing approaches typically achieve behavioral adaptation by revisin…
GGBond: Growing Graph-Based AI-Agent Society for Socially-Aware Recommender Simulation
Hailin Zhong, Hanlin Wang, Yujun Ye +2
Current personalized recommender systems predominantly rely on static offline data for algorithm design and evaluation, significantly limiting their ability to capture long-term us…
Can bidirectional encoder become the ultimate winner for downstream applications of foundation models?
Lewen Yang, Xuanyu Zhou, Juao Fan +2
Over the past few decades, Artificial Intelligence(AI) has progressed from the initial machine learning stage to the deep learning stage, and now to the stage of foundational model…
RCM++:Reverse Cuthill-McKee ordering with Bi-Criteria Node Finder
JiaJun Hou, HongJie Liu, ShengXin Zhu
The Reverse Cuthill-McKee (RCM) algorithm is a graph-based method for reordering sparse matrices, renowned for its effectiveness in minimizing matrix bandwidth and profile. This re…
Movie Recommendation with Poster Attention via Multi-modal Transformer Feature Fusion
Linhan Xia, Yicheng Yang, Ziou Chen +2
Pre-trained models learn general representations from large datsets which can be fine-turned for specific tasks to significantly reduce training time. Pre-trained models like gener…
EchoMamba4Rec: Harmonizing Bidirectional State Space Models with Spectral Filtering for Advanced Sequential Recommendation
Yuda Wang, Xuxin He, Shengxin Zhu
Predicting user preferences and sequential dependencies based on historical behavior is the core goal of sequential recommendation. Although attention-based models have shown effec…
Quantformer: from attention to profit with a quantitative transformer trading strategy
Zhaofeng Zhang, Banghao Chen, Shengxin Zhu +1
In traditional quantitative trading practice, navigating the complicated and dynamic financial market presents a persistent challenge. Fully capturing various market variables, inc…
Native spaces and generalization of Wu functions
Yixuan Huang, Zongmin Wu, Shengxin Zhu
We prove that the native space of a Wu function is a dense subspace of a Sobolev space. An explicit characterization of the native spaces of Wu functions is given. Three definition…
Unleashing the potential of prompt engineering for large language models
Banghao Chen, Zhaofeng Zhang, Nicolas Langrené +1
This comprehensive review delves into the pivotal role of prompt engineering in unleashing the capabilities of Large Language Models (LLMs). The development of Artificial Intellige…