24 citations · 45 across the 21 of their papers we have counts for
6 papers · 1 filter
Toxicity Red-Teaming: Benchmarking LLM Safety in Singapore's Low-Resource Languages
Yujia Hu, Ming Shan Hee, Preslav Nakov +1
The advancement of Large Language Models (LLMs) has transformed natural language processing; however, their safety mechanisms remain under-explored in low-resource, multilingual se…
FRaN-X: FRaming and Narratives-eXplorer
Artur Muratov, Hana Fatima Shaikh, Vanshikaa Jani +21
We present FRaN-X, a Framing and Narratives Explorer that automatically detects entity mentions and classifies their narrative roles directly from raw text. FRaN-X comprises a two-…
Sword and Shield: Uses and Strategies of LLMs in Navigating Disinformation
Gionnieve Lim, Bryan Chen Zhengyu Tan, Kellie Yu Hui Sim +6
The emergence of Large Language Models (LLMs) presents a dual challenge in the fight against disinformation. These powerful tools, capable of generating human-like text at scale, c…
Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia
Samuel Cahyawijaya, Holy Lovenia, Joel Ruben Antony Moniz +89
Southeast Asia (SEA) is a region of extraordinary linguistic and cultural diversity, yet it remains significantly underrepresented in vision-language (VL) research. This often resu…
Shifting Long-Context LLMs Research from Input to Output
Yuhao Wu, Yushi Bai, Zhiqing Hu +4
Recent advancements in long-context Large Language Models (LLMs) have primarily concentrated on processing extended input contexts, resulting in significant strides in long-context…
Demystifying Hateful Content: Leveraging Large Multimodal Models for Hateful Meme Detection with Explainable Decisions
Ming Shan Hee, Roy Ka-Wei Lee
Hateful meme detection presents a significant challenge as a multimodal task due to the complexity of interpreting implicit hate messages and contextual cues within memes. Previous…