24 citations · 45 across the 21 of their papers we have counts for
23 papers
Change the Number, Change the Answer: Assessing Rating Scale Sensitivity in LLM-Based Text Scoring
Wonjeong Jo, Gyuwan Kim, Ming Shan Hee
Large language models (LLMs) are increasingly used in computational social science to assign scalar scores to social and psychological constructs. However, studies use different ra…
SkillGym: Training Skill-Use Agents with Automatic Verifiable Environment Generation
Renxi Wang, Mingshan Hee, Fajri Koto +2
Skills equip LLM agents with professional knowledge and guidance to complete long-horizon and complex tasks. Although skills have been widely adopted in recent agent paradigms and…
TABVERSE: Benchmarking Cross-Format Table Understanding in LLMs and VLMs
Momina Ahsan, Sarfraz Ahmad, Ming Shan Hee +2
Large Language Models (LLMs) and Vision-Language Models (VLMs) are increasingly evaluated on table reasoning tasks, but the role of table representation remains under-explored. In…
K2-V2: A 360-Open, Reasoning-Enhanced LLM
K2 Team, Zhengzhong Liu, Liping Tang +36
We introduce K2-V2, a 360-open LLM built from scratch as a superior base for reasoning adaptation, in addition to functions such as conversation and knowledge retrieval from genera…
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…
Bridging Modalities: Enhancing Cross-Modality Hate Speech Detection with Few-Shot In-Context Learning
Ming Shan Hee, Aditi Kumaresan, Roy Ka-Wei Lee
The widespread presence of hate speech on the internet, including formats such as text-based tweets and vision-language memes, poses a significant challenge to digital platform saf…
LongGenBench: Benchmarking Long-Form Generation in Long Context LLMs
Yuhao Wu, Ming Shan Hee, Zhiqing Hu +1
Current benchmarks like Needle-in-a-Haystack (NIAH), Ruler, and Needlebench focus on models' ability to understand long-context input sequences but fail to capture a critical dimen…
SGHateCheck: Functional Tests for Detecting Hate Speech in Low-Resource Languages of Singapore
Ri Chi Ng, Nirmalendu Prakash, Ming Shan Hee +2
To address the limitations of current hate speech detection models, we introduce \textsf{SGHateCheck}, a novel framework designed for the linguistic and cultural context of Singapo…
Recent Advances in Hate Speech Moderation: Multimodality and the Role of Large Models
Ming Shan Hee, Shivam Sharma, Rui Cao +4
In the evolving landscape of online communication, moderating hate speech (HS) presents an intricate challenge, compounded by the multimodal nature of digital content. This compreh…
Prompting Large Language Models for Topic Modeling
Han Wang, Nirmalendu Prakash, Nguyen Khoi Hoang +3
Topic modeling is a widely used technique for revealing underlying thematic structures within textual data. However, existing models have certain limitations, particularly when dea…
MATK: The Meme Analytical Tool Kit
Ming Shan Hee, Aditi Kumaresan, Nguyen Khoi Hoang +3
The rise of social media platforms has brought about a new digital culture called memes. Memes, which combine visuals and text, can strongly influence public opinions on social and…
PromptMTopic: Unsupervised Multimodal Topic Modeling of Memes using Large Language Models
Nirmalendu Prakash, Han Wang, Nguyen Khoi Hoang +2
The proliferation of social media has given rise to a new form of communication: memes. Memes are multimodal and often contain a combination of text and visual elements that convey…
Pro-Cap: Leveraging a Frozen Vision-Language Model for Hateful Meme Detection
Rui Cao, Ming Shan Hee, Adriel Kuek +3
Hateful meme detection is a challenging multimodal task that requires comprehension of both vision and language, as well as cross-modal interactions. Recent studies have tried to f…
Decoding the Underlying Meaning of Multimodal Hateful Memes
Ming Shan Hee, Wen-Haw Chong, Roy Ka-Wei Lee
Recent studies have proposed models that yielded promising performance for the hateful meme classification task. Nevertheless, these proposed models do not generate interpretable e…
TotalDefMeme: A Multi-Attribute Meme dataset on Total Defence in Singapore
Nirmalendu Prakash, Ming Shan Hee, Roy Ka-Wei Lee
Total Defence is a defence policy combining and extending the concept of military defence and civil defence. While several countries have adopted total defence as their defence pol…
Evaluating GPT-3 Generated Explanations for Hateful Content Moderation
Han Wang, Ming Shan Hee, Md Rabiul Awal +2
Recent research has focused on using large language models (LLMs) to generate explanations for hate speech through fine-tuning or prompting. Despite the growing interest in this ar…
On Explaining Multimodal Hateful Meme Detection Models
Ming Shan Hee, Roy Ka-Wei Lee, Wen-Haw Chong
Hateful meme detection is a new multimodal task that has gained significant traction in academic and industry research communities. Recently, researchers have applied pre-trained v…
Linky: Visualizing User Identity Linkage Results For Multiple Online Social Networks
Roy Ka-Wei Lee, Ming Shan Hee, Philips Kokoh Prasetyo +1
User identity linkage across online social networks is an emerging research topic that has attracted attention in recent years. Many user identity linkage methods have been propose…