Junjie Wu

Ph.D. candidate at HKUST

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junjie.wu@connect.ust.hk

Preprint

Understanding LLMs Fluid Intelligence Deficiency: An Analysis of the ARC Task
Junjie Wu, Mo Yu, Lemao Liu, Dit-Yan Yeung and Jie Zhou

Paper | Code

The Stochastic Parrot on LLM’s Shoulder: A Summative Assessment of Physical Concept Understanding
Mo Yu*, Lemao Liu*, Junjie Wu*, Tsz Ting Chung*, Shunchi Zhang*, Jiangnan Li, Dit-Yan Yeung and Jie Zhou

Paper | Code

Unified Triplet-Level Hallucination Evaluation for Large Vision-Language Models
Junjie Wu*, Tsz Ting Chung*, Kai Chen* and Dit-Yan Yeung

Paper | Code

Accepted

Rethinking Targeted Adversarial Attacks for Neural Machine Translation
Junjie Wu, Lemao Liu, Wei Bi, and Dit-Yan Yeung
ICASSP 2024
Paper | Code

Towards General Error Diagnosis via Behavioral Testing in Machine Translation
Junjie Wu, Lemao Liu and Dit-Yan Yeung
EMNLP 2023.
(Presented at the GenBench workshop at EMNLP 2023.)
Paper | Code

Conversations Gone Alright: Quantifying and Predicting Prosocial Outcomes in Online Conversations
Jiajun Bao*, Junjie Wu*, Yiming Zhang*, Eshwar Chandrasekharan and David Jurgens
The Web Conference (WWW) 2021 (*:Equal contribution. The order is alphabetical.)
Paper | Code

Augmenting Topic Aware Knowledge-Grounded Conversations with Dynamic Built Knowledge Graphs
Junjie Wu and Hao Zhou
DeeLIO workshop, NAACL 2021.
Paper | Code

We examine the extent to which participation in high school athletics has beneficial effects on future education, labor market, and health outcomes. Due to the absence of plausible instruments in observational data, we use recently developed methods that relate selection on observables with selection on unobservables to estimate bounds on the causal effect of athletics participation. We analyze these effects in the US separately for men and women using three different nationally representative longitudinal data sets that each link high school athletics participation with later-life outcomes. We do not find consistent evidence of individual benefits reported in many previous studies—once we have accounted for selection, high school athletes are no more likely to attend college, earn higher wages, or participate in the labor force. However, we do find that men (but not women) who participated in high school athletics are more likely to exercise regularly as adults. Nevertheless, athletes are no less likely to be obese.

Manuscript

SCAT: Robust Self-supervised Contrastive Learning via Adversarial Training for Text Classification
Junjie Wu and Dit-Yan Yeung
Paper | Code

We examine the extent to which participation in high school athletics has beneficial effects on future education, labor market, and health outcomes. Due to the absence of plausible instruments in observational data, we use recently developed methods that relate selection on observables with selection on unobservables to estimate bounds on the causal effect of athletics participation. We analyze these effects in the US separately for men and women using three different nationally representative longitudinal data sets that each link high school athletics participation with later-life outcomes. We do not find consistent evidence of individual benefits reported in many previous studies—once we have accounted for selection, high school athletes are no more likely to attend college, earn higher wages, or participate in the labor force. However, we do find that men (but not women) who participated in high school athletics are more likely to exercise regularly as adults. Nevertheless, athletes are no less likely to be obese.