activity
20192026
most citedCoAnnotating: Uncertainty-Guided Work Allocation between Human and Large Language Models for Data Annotation

43 citations · 83 across the 40 of their papers we have counts for

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Showing 2025 · cs.CLShow all

5 papers · 2 filters

cs.CL2025

Persuasion Dynamics in LLMs: Investigating Robustness and Adaptability in Knowledge and Safety with DuET-PD

Bryan Chen Zhengyu Tan, Daniel Wai Kit Chin, Zhengyuan Liu +2

Large Language Models (LLMs) can struggle to balance gullibility to misinformation and resistance to valid corrections in persuasive dialogues, a critical challenge for reliable de…

cs.CL2025

COGENT: A Curriculum-oriented Framework for Generating Grade-appropriate Educational Content

Zhengyuan Liu, Stella Xin Yin, Dion Hoe-Lian Goh +1

While Generative AI has demonstrated strong potential and versatility in content generation, its application to educational contexts presents several challenges. Models often fail…

cs.CL2025

SingaKids: A Multilingual Multimodal Dialogic Tutor for Language Learning

Zhengyuan Liu, Geyu Lin, Hui Li Tan +8

The integration of generative artificial intelligence into educational applications has enhanced personalized and interactive learning experiences, and it shows strong potential to…

cs.CL2025

Integrating Video and Text: A Balanced Approach to Multimodal Summary Generation and Evaluation

Galann Pennec, Zhengyuan Liu, Nicholas Asher +2

Vision-Language Models (VLMs) often struggle to balance visual and textual information when summarizing complex multimodal inputs, such as entire TV show episodes. In this paper, w…

cs.CL2025

MERaLiON-TextLLM: Cross-Lingual Understanding of Large Language Models in Chinese, Indonesian, Malay, and Singlish

Xin Huang, Tarun Kumar Vangani, Minh Duc Pham +4

Multilingual large language models (MLLMs) have shown impressive capabilities across a variety of languages. However, efficacy can differ greatly between different language familie…