Papers by Jihong Wang
Extracting Topics with Simultaneous Word Co-occurrence and Semantic Correlation Graphs: Neural Topic Modeling for Short Texts (2021.findings-emnlp)
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| Challenge: | Empirical results validate that DWGTM can generate more semantically coherent topics than baseline topic models. |
| Approach: | They develop a neural topic model which extracts topics from word co-occurrence graphs . Empirical results validate that DWGTM can generate more semantically coherent topics than baseline topic models. |
| Outcome: | Empirical results show that the proposed model can generate more coherent topics than baseline topic models. |
We Need to Talk About Reproducibility in NLP Model Comparison (2023.emnlp-main)
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| Challenge: | Existing studies show that standard splits produce low reproducible and unreliable conclusions . reproducibility of empirical experimental conclusions is a problem in NLP domain . |
| Approach: | They propose to transform the reproducibility of a model comparison into a probabilistic function . they propose to use a regularized corpus splitting strategy to estimate the model's performance . |
| Outcome: | The proposed estimator achieves a high SNR and significantly increases reproducibility. |
Bayes Test of Precision, Recall, and F1 Measure for Comparison of Two Natural Language Processing Models (P19-1)
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| Challenge: | Existing t-tests for cross-validation (CV) are inappropriate for model comparison . existing t tests for cross validation (CV), such as 52 CV t test and F ttest, are inadequate . |
| Approach: | They propose to use a block-regularized 32 CV to compare two NLP models . they calibrate the posterior distributions of P, R, and F1 and derive an accurate interval estimation of P and R . |
| Outcome: | The proposed model could regularize the difference in certain frequency distributions over linguistic units and yield stable estimators of P, R, and F1. |
ColorBrowserAgent: Complex Long-Horizon Browser Agent with Adaptive Knowledge Evolution (2026.acl-industry)
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Jihong Wang, Jiamu Zhou, Weiming Zhang, Teng Wang, Weiwen Liu, Zhuosheng Zhang, Xingyu Lou, Weinan Zhang, Huarong Deng, Jun Wang
| Challenge: | Xue et al., 2025): deploying autonomous web agents in production remains difficult due to site heterogeneity and long-horizon instability. |
| Approach: | They propose a knowledge-evolving agent that can be used to automate web workflows . they use human-in-the-loop knowledge adaptation and knowledge-aligned progressive summarization . |
| Outcome: | Experiments on WebArena, WebChoreAren and industrial deployment show it outperforms baselines. |