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20232025
most citedRecent Advances in Multimodal Affective Computing: An NLP Perspective

4 citations · 8 across the 7 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.LG2024

Correcting Large Language Model Behavior via Influence Function

Han Zhang, Zhuo Zhang, Yi Zhang +8

Recent advancements in AI alignment techniques have significantly improved the alignment of large language models (LLMs) with static human preferences. However, the dynamic nature…

cs.CL2024★ 4 cited

Recent Advances in Multimodal Affective Computing: An NLP Perspective

Guimin Hu, Weimin Lyu, Chang Sun +5

Multimodal affective computing has gained increasing attention due to its broad applications in understanding human behavior and intentions, particularly in text-centric multimodal…

cs.CL2024★ 1 cited

Multi-modal Stance Detection: New Datasets and Model

Bin Liang, Ang Li, Jingqian Zhao +5

Stance detection is a challenging task that aims to identify public opinion from social media platforms with respect to specific targets. Previous work on stance detection largely…

cs.CL2024★ 1 cited

Mitigating Biases of Large Language Models in Stance Detection with Counterfactual Augmented Calibration

Ang Li, Jingqian Zhao, Bin Liang +6

Stance detection is critical for understanding the underlying position or attitude expressed toward a topic. Large language models (LLMs) have demonstrated significant advancements…

cs.LG2024★ 2 cited

COPR: Continual Human Preference Learning via Optimal Policy Regularization

Han Zhang, Lin Gui, Yu Lei +8

Reinforcement Learning from Human Feedback (RLHF) is commonly utilized to improve the alignment of Large Language Models (LLMs) with human preferences. Given the evolving nature of…