activity
20242026
most citedContinual Learning of Large Language Models: A Comprehensive Survey

12 citations · 13 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IR2026

Generative Retrieval for E-commerce: Jointly Learning Embedding and Codebook with Same Product Cluster

Songtao Fang, Zihao Xu, Shaowei Wei +2

With the development of large language models (LLMs), generative retrieval is becoming increasingly important in e-commerce scenarios. Current mainstream approaches typically use a…

cs.IR2026

Probabilistic Residual Learning for Online Recommendations

Wenyuan Wang, Yusong Zhao, Zihao Xu +11

Modern recommender systems are typically based on deep learning (DL) models, where a dense encoder learns representations of users and items. As a result, these systems often suffe…

cs.CL2026

Compressing Sequences in the Latent Embedding Space: -Token Merging for Large Language Models

Zihao Xu, John Harvill, Ziwei Fan +3

Large Language Models (LLMs) incur significant computational and memory costs when processing long prompts, as full self-attention scales quadratically with input length. Token com…

cs.AI2025

GenVP: Generating Visual Puzzles with Contrastive Hierarchical VAEs

Kalliopi Basioti, Pritish Sahu, Qingze Tony Liu +3

Raven's Progressive Matrices (RPMs) is an established benchmark to examine the ability to perform high-level abstract visual reasoning (AVR). Despite the current success of algorit…

cs.CV2025

Rate-My-LoRA: Efficient and Adaptive Federated Model Tuning for Cardiac MRI Segmentation

Xiaoxiao He, Haizhou Shi, Ligong Han +7

Cardiovascular disease (CVD) and cardiac dyssynchrony are major public health problems in the United States. Precise cardiac image segmentation is crucial for extracting quantitati…

cs.LG2024★ 1 cited

Implicit In-context Learning

Zhuowei Li, Zihao Xu, Ligong Han +5

In-context Learning (ICL) empowers large language models (LLMs) to swiftly adapt to unseen tasks at inference-time by prefixing a few demonstration examples before queries. Despite…

cs.LG2024★ 12 cited

Continual Learning of Large Language Models: A Comprehensive Survey

Haizhou Shi, Zihao Xu, Hengyi Wang +6

The recent success of large language models (LLMs) trained on static, pre-collected, general datasets has sparked numerous research directions and applications. One such direction…