most citedMIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization

1 citations · 1 across the 2 of their papers we have counts for

collaborators

6 papers

cs.SI2025

Deep Identification of Propagation Trees

Zeeshan Memon, Chen Ling, Ruochen Kong +3

Understanding propagation structures in graph diffusion processes, such as epidemic spread or misinformation diffusion, is a fundamental yet challenging problem. While existing met…

cs.SI2024

Source Localization for Cross Network Information Diffusion

Chen Ling, Tanmoy Chowdhury, Jie Ji +3

Source localization aims to locate information diffusion sources only given the diffusion observation, which has attracted extensive attention in the past few years. Existing metho…

cs.SI20241 cited

MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization

Nguyen Do, Tanmoy Chowdhury, Chen Ling +2

Multiplex influence maximization (MIM) asks us to identify a set of seed users such as to maximize the expected number of influenced users in a multiplex network. MIM has been one…

cs.CL2024

ELAD: Explanation-Guided Large Language Models Active Distillation

Yifei Zhang, Bo Pan, Chen Ling +2

The deployment and application of Large Language Models (LLMs) is hindered by their memory inefficiency, computational demands, and the high costs of API inferences. Traditional di…

cs.CL2024

SparseLLM: Towards Global Pruning for Pre-trained Language Models

Guangji Bai, Yijiang Li, Chen Ling +2

The transformative impact of large language models (LLMs) like LLaMA and GPT on natural language processing is countered by their prohibitive computational demands. Pruning has eme…

cs.CL2024

A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Models

Mingchen Li, Chen Ling, Rui Zhang +1

Zero-shot link prediction (ZSLP) on knowledge graphs aims at automatically identifying relations between given entities. Existing methods primarily employ auxiliary information to…