23 citations · 75 across the 26 of their papers we have counts for
16 papers · 1 filter
From Interpretability to Control: Insights from Six Years of the TrustNLP Workshop
Rahul Gupta, Abhinav Mohanty, Anaelia Ovalle +10
The Workshop on Trustworthy Natural Language Processing (TrustNLP), co-located with major ACL conferences since 2021, has grown from 8 proceedings papers to 41 over six editions, d…
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…
Can LLMs Improve Multimodal Fact-Checking by Asking Relevant Questions?
Alimohammad Beigi, Bohan Jiang, Dawei Li +5
Traditional fact-checking relies on humans to formulate relevant and targeted fact-checking questions (FCQs), search for evidence, and verify the factuality of claims. While Large…
Navigating the Shadows: Unveiling Effective Disturbances for Modern AI Content Detectors
Ying Zhou, Ben He, Le Sun
With the launch of ChatGPT, large language models (LLMs) have attracted global attention. In the realm of article writing, LLMs have witnessed extensive utilization, giving rise to…
Defending Against Social Engineering Attacks in the Age of LLMs
Lin Ai, Tharindu Kumarage, Amrita Bhattacharjee +12
The proliferation of Large Language Models (LLMs) poses challenges in detecting and mitigating digital deception, as these models can emulate human conversational patterns and faci…
Harnessing Artificial Intelligence to Combat Online Hate: Exploring the Challenges and Opportunities of Large Language Models in Hate Speech Detection
Tharindu Kumarage, Amrita Bhattacharjee, Joshua Garland
Large language models (LLMs) excel in many diverse applications beyond language generation, e.g., translation, summarization, and sentiment analysis. One intriguing application is…
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…
How Reliable Are AI-Generated-Text Detectors? An Assessment Framework Using Evasive Soft Prompts
Tharindu Kumarage, Paras Sheth, Raha Moraffah +2
In recent years, there has been a rapid proliferation of AI-generated text, primarily driven by the release of powerful pre-trained language models (PLMs). To address the issue of…
ConDA: Contrastive Domain Adaptation for AI-generated Text Detection
Amrita Bhattacharjee, Tharindu Kumarage, Raha Moraffah +1
Large language models (LLMs) are increasingly being used for generating text in a variety of use cases, including journalistic news articles. Given the potential malicious nature i…
J-Guard: Journalism Guided Adversarially Robust Detection of AI-generated News
Tharindu Kumarage, Amrita Bhattacharjee, Djordje Padejski +5
The rapid proliferation of AI-generated text online is profoundly reshaping the information landscape. Among various types of AI-generated text, AI-generated news presents a signif…
Neural Authorship Attribution: Stylometric Analysis on Large Language Models
Tharindu Kumarage, Huan Liu
Large language models (LLMs) such as GPT-4, PaLM, and Llama have significantly propelled the generation of AI-crafted text. With rising concerns about their potential misuse, there…
Causality Guided Disentanglement for Cross-Platform Hate Speech Detection
Paras Sheth, Tharindu Kumarage, Raha Moraffah +2
Social media platforms, despite their value in promoting open discourse, are often exploited to spread harmful content. Current deep learning and natural language processing models…
PEACE: Cross-Platform Hate Speech Detection- A Causality-guided Framework
Paras Sheth, Tharindu Kumarage, Raha Moraffah +2
Hate speech detection refers to the task of detecting hateful content that aims at denigrating an individual or a group based on their religion, gender, sexual orientation, or othe…
Stylometric Detection of AI-Generated Text in Twitter Timelines
Tharindu Kumarage, Joshua Garland, Amrita Bhattacharjee +3
Recent advancements in pre-trained language models have enabled convenient methods for generating human-like text at a large scale. Though these generation capabilities hold great…
Towards Detecting Harmful Agendas in News Articles
Melanie Subbiah, Amrita Bhattacharjee, Yilun Hua +3
Manipulated news online is a growing problem which necessitates the use of automated systems to curtail its spread. We argue that while misinformation and disinformation detection…