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20242026
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cs.CL2026

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024

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…

cs.CL2024

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…