1 code implementation • 17 Apr 2024 • Zhiheng Lyu, Zhijing Jin, Fernando Gonzalez, Rada Mihalcea, Bernhard Schoelkopf, Mrinmaya Sachan
Sentiment analysis (SA) aims to identify the sentiment expressed in a text, such as a product review.
no code implementations • 12 Mar 2024 • Zhiheng Lyu, Jiannan Yang, Zhongzhi Xu, Weilan Wang, Weibin Cheng, Kwok-Leung Tsui, Gary Tse, Qingpeng Zhang
The model integrates drug-protein-disease pathways and real-world clinical data of AF patients to generate the IS risk and potential pathways for each patient.
1 code implementation • NeurIPS 2023 • Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng Lyu, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, Bernhard Schölkopf
Much of the existing work in natural language processing (NLP) focuses on evaluating commonsense causal reasoning in LLMs, thus failing to assess whether a model can perform causal inference in accordance with a set of well-defined formal rules.
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).
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.
1 code implementation • 2 May 2023 • Zhiheng Lyu, Zhijing Jin, Justus Mattern, Rada Mihalcea, Mrinmaya Sachan, Bernhard Schoelkopf
In this work, we take sentiment classification as an example and look into the causal relations between the review (X) and sentiment (Y).
2 code implementations • 28 Feb 2022 • Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, Xiaoyu Shen, Yiwen Ding, Zhiheng Lyu, Mrinmaya Sachan, Rada Mihalcea, Bernhard Schölkopf
In this paper, we propose the task of logical fallacy detection, and provide a new dataset (Logic) of logical fallacies generally found in text, together with an additional challenge set for detecting logical fallacies in climate change claims (LogicClimate).
no code implementations • 2 Sep 2021 • Hongyin Zhu, Hao Peng, Zhiheng Lyu, Lei Hou, Juanzi Li, Jinghui Xiao
In this paper, we propose a heterogeneous knowledge language model (\textbf{HKLM}), a unified pre-trained language model (PLM) for all forms of text, including unstructured text, semi-structured text, and well-structured text.