activity
20192022
most citedInvestigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach

1 citations · 1 across the 5 of their papers we have counts for

collaborators

9 papers

cs.CY20221 cited

Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach

Jiayao Zhang, Hongming Zhang, Zhun Deng +1

Double-blind peer review mechanism has become the skeleton of academic research across multiple disciplines including computer science, yet several studies have questioned the qual…

cs.CL2022

METGEN: A Module-Based Entailment Tree Generation Framework for Answer Explanation

Ruixin Hong, Hongming Zhang, Xintong Yu +1

Knowing the reasoning chains from knowledge to the predicted answers can help construct an explainable question answering (QA) system. Advances on QA explanation propose to explain…

cs.CL2021

Benchmarking Commonsense Knowledge Base Population with an Effective Evaluation Dataset

Tianqing Fang, Weiqi Wang, Sehyun Choi +4

Reasoning over commonsense knowledge bases (CSKB) whose elements are in the form of free-text is an important yet hard task in NLP. While CSKB completion only fills the missing lin…

cs.CL2021

Learning Constraints and Descriptive Segmentation for Subevent Detection

Haoyu Wang, Hongming Zhang, Muhao Chen +1

Event mentions in text correspond to real-world events of varying degrees of granularity. The task of subevent detection aims to resolve this granularity issue, recognizing the mem…

cs.CL2021

Exophoric Pronoun Resolution in Dialogues with Topic Regularization

Xintong Yu, Hongming Zhang, Yangqiu Song +3

Resolving pronouns to their referents has long been studied as a fundamental natural language understanding problem. Previous works on pronoun coreference resolution (PCR) mostly f…

cs.CL2021

Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schema

Yanai Elazar, Hongming Zhang, Yoav Goldberg +1

The Winograd Schema (WS) has been proposed as a test for measuring commonsense capabilities of models. Recently, pre-trained language model-based approaches have boosted performanc…