activity
20212026
most citedA Coarse-to-fine Cascaded Evidence-Distillation Neural Network for Explainable Fake News Detection

10 citations · 13 across the 9 of their papers we have counts for

collaborators

11 papers

cs.CL2026

SRJudge: Empowering Large Language Models with Selective Reasoning for Fine-Grained Knowledge Concept Tagging

Zhiwei Yang, Jiahua Yang, Huiru Lin +2

Knowledge concept tagging aims to assign specific concept or topic labels to educational content, which is essential for both educators and learners in traditional and online teach…

cs.AI2026

Learn from the Gap: Differential-Aware Advantage Pruning with Adaptive Rollout Sampling for GRPO

Jiahua Yang, Zhiwei Yang, Xianpeng Zhang +7

Recently, Group Relative Policy Optimization (GRPO) and its variants have been developed for policy optimization and demonstrated notable performance gains. However, these methods…

cs.CL2026

A Graph-Enhanced Defense Framework for Explainable Fake News Detection with LLM

Bo Wang, Jing Ma, Hongzhan Lin +4

Explainable fake news detection aims to assess the veracity of news claims while providing human-friendly explanations. Existing methods incorporating investigative journalism are…

cs.CL2024

Explainable Fake News Detection With Large Language Model via Defense Among Competing Wisdom

Bo Wang, Jing Ma, Hongzhan Lin +4

Most fake news detection methods learn latent feature representations based on neural networks, which makes them black boxes to classify a piece of news without giving any justific…

cs.CL2023

WSDMS: Debunk Fake News via Weakly Supervised Detection of Misinforming Sentences with Contextualized Social Wisdom

Ruichao Yang, Wei Gao, Jing Ma +2

In recent years, we witness the explosion of false and unconfirmed information (i.e., rumors) that went viral on social media and shocked the public. Rumors can trigger versatile,…

cs.CL2023★ 2 cited

A Unified Contrastive Transfer Framework with Propagation Structure for Boosting Low-Resource Rumor Detection

Hongzhan Lin, Jing Ma, Ruichao Yang +2

The truth is significantly hampered by massive rumors that spread along with breaking news or popular topics. Since there is sufficient corpus gathered from the same domain for mod…

cs.CL2022★ 10 cited

A Coarse-to-fine Cascaded Evidence-Distillation Neural Network for Explainable Fake News Detection

Zhiwei Yang, Jing Ma, Hechang Chen +3

Existing fake news detection methods aim to classify a piece of news as true or false and provide veracity explanations, achieving remarkable performances. However, they often tail…

cs.LG2022

The Sufficiency of Off-Policyness and Soft Clipping: PPO is still Insufficient according to an Off-Policy Measure

Xing Chen, Dongcui Diao, Hechang Chen +7

The popular Proximal Policy Optimization (PPO) algorithm approximates the solution in a clipped policy space. Does there exist better policies outside of this space? By using a nov…

cs.CL2022

DecBERT: Enhancing the Language Understanding of BERT with Causal Attention Masks

Ziyang Luo, Yadong Xi, Jing Ma +4

Since 2017, the Transformer-based models play critical roles in various downstream Natural Language Processing tasks. However, a common limitation of the attention mechanism utiliz…

cs.CL2022

Detect Rumors in Microblog Posts for Low-Resource Domains via Adversarial Contrastive Learning

Hongzhan Lin, Jing Ma, Liangliang Chen +3

Massive false rumors emerging along with breaking news or trending topics severely hinder the truth. Existing rumor detection approaches achieve promising performance on the yester…

cs.CL2021★ 1 cited

Rumor Detection on Twitter with Claim-Guided Hierarchical Graph Attention Networks

Hongzhan Lin, Jing Ma, Mingfei Cheng +3

Rumors are rampant in the era of social media. Conversation structures provide valuable clues to differentiate between real and fake claims. However, existing rumor detection metho…