1 citations · 1 across the 4 of their papers we have counts for
5 papers
ExTax: Explainable Disinformation Detection via Persuasion, Emotion, and Narrative Role Taxonomies
Shang Luo, Yingguang Yang, Zhenchen Sun +8
The democratization of LLMs has accelerated the generation and circulation of highly fluent disinformation, making traditional syntax-semantic verification increasingly insufficien…
VisualNeedle: Benchmarking Active Visual Search in Information-Dense Scenes
Jingru Chen, Yiming Liu, Mingtao Chen +5
Frontier multimodal large language models (MLLMs) have been reported to achieve over 90\% accuracy on fine-grained perception benchmarks. However, such scores do not necessarily im…
DVD: A Robust Method for Detecting Variant Contamination in Large Language Model Evaluation
Renzhao Liang, Jingru Chen, Bo Jia +7
Evaluating large language models (LLMs) is increasingly confounded by \emph{variant contamination}: the training corpus contains semantically equivalent yet lexically or syntactica…
Abstain Mask Retain Core: Time Series Prediction by Adaptive Masking Loss with Representation Consistency
Renzhao Liang, Sizhe Xu, Chenggang Xie +4
Time series forecasting plays a pivotal role in critical domains such as energy management and financial markets. Although deep learning-based approaches (e.g., MLP, RNN, Transform…
Getting Serious about Humor: Crafting Humor Datasets with Unfunny Large Language Models
Zachary Horvitz, Jingru Chen, Rahul Aditya +4
Humor is a fundamental facet of human cognition and interaction. Yet, despite recent advances in natural language processing, humor detection remains a challenging task that is com…