Papers by Sirry Chen

2 papers
CACL: Community-Aware Heterogeneous Graph Contrastive Learning for Social Media Bot Detection (2024.findings-acl)

Copied to clipboard

Challenge: Existing methods for social media bot detection neglect community structure and poor model generalization due to the relatively small scale of the dataset.
Approach: They propose a framework that constructs social networks as heterogeneous graphs and uses community-aware modules to mine hard positive and hard negative samples for supervised graph contrastive learning.
Outcome: The proposed framework outperforms baselines on three social media bot benchmarks.
SpeechMedAssist: Efficiently and Effectively Adapting Speech Language Models for Medical Consultation (2026.acl-long)

Copied to clipboard

Challenge: Recent advances in speech language models have enabled more natural speech-based interactions, but the scarcity of medical speech data and the inefficiency of fine-tuning on speech data hinder adoption of SpeechLMs in medical consultation.
Approach: They propose a SpeechLM natively capable of conducting speech-based multi-turn interactions with patients.
Outcome: The proposed model outperforms baselines in both effectiveness and robustness in most evaluation settings.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations