activity
20222024
most citedCausal Intervention Improves Implicit Sentiment Analysis

9 citations · 21 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024

In-Memory Learning: A Declarative Learning Framework for Large Language Models

Bo Wang, Tianxiang Sun, Hang Yan +3

The exploration of whether agents can align with their environment without relying on human-labeled data presents an intriguing research topic. Drawing inspiration from the alignme…

cs.CL20244 cited

Domain Generalization via Causal Adjustment for Cross-Domain Sentiment Analysis

Siyin Wang, Jie Zhou, Qin Chen +3

Domain adaption has been widely adapted for cross-domain sentiment analysis to transfer knowledge from the source domain to the target domain. Whereas, most methods are proposed un…

cs.CL2024

LLM can Achieve Self-Regulation via Hyperparameter Aware Generation

Siyin Wang, Shimin Li, Tianxiang Sun +6

In the realm of Large Language Models (LLMs), users commonly employ diverse decoding strategies and adjust hyperparameters to control the generated text. However, a critical questi…

cs.CL20238 cited

Evaluating Hallucinations in Chinese Large Language Models

Qinyuan Cheng, Tianxiang Sun, Wenwei Zhang +8

In this paper, we establish a benchmark named HalluQA (Chinese Hallucination Question-Answering) to measure the hallucination phenomenon in Chinese large language models. HalluQA c…

cs.CL20229 cited

Causal Intervention Improves Implicit Sentiment Analysis

Siyin Wang, Jie Zhou, Changzhi Sun +4

Despite having achieved great success for sentiment analysis, existing neural models struggle with implicit sentiment analysis. This may be due to the fact that they may latch onto…