Papers by Jiaqian Liu
Dual-Path Counterfactual Integration for Multimodal Aspect-Based Sentiment Classification (2025.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods for multimodal aspect-based sentiment classification rely on superficial correlations and spurious cues. |
| Approach: | They propose a Dual-Path Counterfactual Integration framework that explicitly models counterfactual reasoning in multimodal contexts. |
| Outcome: | The proposed framework improves model robustness by explicitly modeling counterfactual reasoning in multimodal contexts. |
Com2 : A Causal-Guided Benchmark for Exploring Complex Commonsense Reasoning in Large Language Models (2025.acl-long)
Copied to clipboard
Kai Xiong, Xiao Ding, Yixin Cao, Yuxiong Yan, Li Du, Yufei Zhang, Jinglong Gao, Jiaqian Liu, Bing Qin, Ting Liu
| Challenge: | Existing works focus on complex tasks like math and code, while complex commonsense reasoning remains underexplored due to its uncertainty and lack of structure. |
| Approach: | They propose to build a benchmark for large language models based on complex commonsense reasoning based upon causal event graphs and causal theory. |
| Outcome: | The proposed benchmark combines a complex commonsense reasoning benchmark with a detective story to achieve a more challenging subset. |