Bias Amplification Enhances Minority Group Performance

1 code implementation • 13 Sep 2023 • Gaotang Li, Jiarui Liu, Wei Hu

Neural networks produced by standard training are known to suffer from poor accuracy on rare subgroups despite achieving high accuracy on average, due to the correlations between certain spurious features and labels.

Interactive Molecular Discovery with Natural Language

1 code implementation • 21 Jun 2023 • Zheni Zeng, Bangchen Yin, Shipeng Wang, Jiarui Liu, Cheng Yang, Haishen Yao, Xingzhi Sun, Maosong Sun, Guotong Xie, Zhiyuan Liu

Natural language is expected to be a key medium for various human-machine interactions in the era of large language models.

Property Prediction

Can Large Language Models Infer Causation from Correlation?

1 code implementation • 9 Jun 2023 • Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona Diab, Bernhard Schölkopf

In this work, we propose the first benchmark dataset to test the pure causal inference skills of large language models (LLMs).

Causal Inference

Voices of Her: Analyzing Gender Differences in the AI Publication World

1 code implementation • 24 May 2023 • Yiwen Ding, Jiarui Liu, Zhiheng Lyu, Kun Zhang, Bernhard Schoelkopf, Zhijing Jin, Rada Mihalcea

While several previous studies have analyzed gender bias in research, we are still missing a comprehensive analysis of gender differences in the AI community, covering diverse topics and different development trends.

Sequential Search Models: A Pairwise Maximum Rank Approach

no code implementations • 28 Apr 2021 • Jiarui Liu

Additionally, we can use the PMR estimator to test for the true match value distribution in the data.