10 citations · 30 across the 45 of their papers we have counts for
5 papers · 1 filter
Exploring Knowledge Purification in Multi-Teacher Knowledge Distillation for LLMs
Ruihan Jin, Pengpeng Shao, Zhengqi Wen +5
Knowledge distillation has emerged as a pivotal technique for transferring knowledge from stronger large language models (LLMs) to smaller, more efficient models. However, traditio…
Atlas: Orchestrating Heterogeneous Models and Tools for Multi-Domain Complex Reasoning
Jinyang Wu, Guocheng Zhai, Ruihan Jin +5
The integration of large language models (LLMs) with external tools has significantly expanded the capabilities of AI agents. However, as the diversity of both LLMs and tools incre…
Debunk and Infer: Multimodal Fake News Detection via Diffusion-Generated Evidence and LLM Reasoning
Kaiying Yan, Moyang Liu, Yukun Liu +4
The rapid spread of fake news across multimedia platforms presents serious challenges to information credibility. In this paper, we propose a Debunk-and-Infer framework for Fake Ne…
Fake News Detection and Manipulation Reasoning via Large Vision-Language Models
Ruihan Jin, Ruibo Fu, Zhengqi Wen +3
Fake news becomes a growing threat to information security and public opinion with the rapid sprawl of media manipulation. Therefore, fake news detection attracts widespread attent…
Progressive Distillation Based on Masked Generation Feature Method for Knowledge Graph Completion
Cunhang Fan, Yujie Chen, Jun Xue +3
In recent years, knowledge graph completion (KGC) models based on pre-trained language model (PLM) have shown promising results. However, the large number of parameters and high co…