18 citations · 36 across the 12 of their papers we have counts for
6 papers · 1 filter
EssayCBM: Rubric-Aligned Concept Bottleneck Models for Transparent Essay Grading
Kumar Satvik Chaudhary, Chengshuai Zhao, Fan Zhang +3
Automated essay scoring (AES) has advanced significantly with neural language models, yet most systems remain opaque, offering little visibility into how grades are produced. In ed…
Domain Knowledge-Enhanced LLMs for Fraud and Concept Drift Detection
Ali Şenol, Garima Agrawal, Huan Liu
Detecting deceptive conversations on dynamic platforms is increasingly difficult due to evolving language patterns and Concept Drift (CD)-i.e., semantic or topical shifts that alte…
Joint Detection of Fraud and Concept Drift inOnline Conversations with LLM-Assisted Judgment
Ali Senol, Garima Agrawal, Huan Liu
Detecting fake interactions in digital communication platforms remains a challenging and insufficiently addressed problem. These interactions may appear as harmless spam or escalat…
RedditESS: A Mental Health Social Support Interaction Dataset -- Understanding Effective Social Support to Refine AI-Driven Support Tools
Zeyad Alghamdi, Tharindu Kumarage, Garima Agrawal +3
Effective mental health support is crucial for alleviating psychological distress. While large language model (LLM)-based assistants have shown promise in mental health interventio…
A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization
Tharindu Kumarage, Garima Agrawal, Paras Sheth +4
We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs) capable of generating high-quality text. While these LLMs have revolutionized text generatio…
Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Survey
Garima Agrawal, Tharindu Kumarage, Zeyad Alghamdi +1
The contemporary LLMs are prone to producing hallucinations, stemming mainly from the knowledge gaps within the models. To address this critical limitation, researchers employ dive…