LLM | Academic

Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models

As large language models (LLMs) transition from research prototypes to real-world systems, customization has emerged as a central …

Liangwei Yang, Shiyu Wang, Haolin Chen, Rithesh Murthy, Ming Zhu, Jielin Qiu, Zixiang Chen, Juntao Tan, Jianguo Zhang, Zhiwei Liu, Wenting Zhao, Silvio Savarese, Caiming Xiong, Huan Wang, Shelby Heinecke

Entropy-Based Block Pruning for Efficient Large Language Models

As large language models continue to scale, their growing computational and storage demands pose significant challenges for real-world …

Liangwei Yang, Yuhui Xu, Juntao Tan, Doyen Sahoo, Silvio Savarese, Caiming Xiong, Huan Wang, Shelby Heinecke

Llminit: A free lunch from large language models for selective initialization of recommendation

Collaborative filtering (CF) is widely adopted in industrial recommender systems (RecSys) for modeling user-item interactions across …

Weizhi Zhang, Liangwei Yang, Wooseong Yang, Henry Peng Zou, Yuqing Liu, Ke Xu, Sourav Medya, Philip S Yu

Personabench: Evaluating ai models on understanding personal information through accessing (synthetic) private user data

Personalization is essential for AI assistants, especially in private AI settings where models are expected to interpret users’ …

Juntao Tan, Liangwei Yang, Zuxin Liu, Zhiwei Liu, Rithesh RN, Tulika Manoj Awalgaonkar, Jianguo Zhang, Weiran Yao, Ming Zhu, Shirley Kokane, Silvio Savarese, Huan Wang, Caiming Xiong, Shelby Heinecke

Training Large Recommendation Models via Graph-Language Tokens Alignment

Recommender systems (RS) have become essential tools for helping users efficiently navigate the overwhelming amount of information on …

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

Benchmarking llms for political science: A united nations perspective

Large Language Models (LLMs) have achieved significant advances in natural language processing, yet their potential for high-stake …

Yueqing Liang, Liangwei Yang, Chen Wang, Congying Xia, Rui Meng, Xiongxiao Xu, Haoran Wang, Ali Payani, Kai Shu

Graph-sequential alignment and uniformity: Toward enhanced recommendation systems

Graph-based and sequential methods are two popular recommendation paradigms, each excelling in its domain but lacking the ability to …

Yuwei Cao, Liangwei Yang, Zhiwei Liu, Yuqing Liu, Chen Wang, Yueqing Liang, Hao Peng, Philip S. Yu

Taxonomy-guided zero-shot recommendations with llms

With the emergence of large language models (LLMs) and their ability to perform a variety of tasks, their application in recommender …

Yueqing Liang, Liangwei Yang, Chen Wang, Xiongxiao Xu, Philip S. Yu, Kai Shu

Apigen: Automated pipeline for generating verifiable and diverse function-calling datasets

The advancement of function-calling agent models requires diverse, reliable, and high-quality datasets. This paper presents APIGen, an …

Zuxin Liu, Thai Hoang, Jianguo Zhang, Ming Zhu, Tian Lan, Juntao Tan, Weiran Yao, Zhiwei Liu, Yihao Feng, Rithesh RN, Liangwei Yang, Silvio Savarese, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong