2 citations · 6 across the 6 of their papers we have counts for
6 papers
StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding
Cheng Jiayang, Lin Qiu, Tsz Ho Chan +9
Analogy-making between narratives is crucial for human reasoning. In this paper, we evaluate the ability to identify and generate analogies by constructing a first-of-its-kind larg…
Gold: A Global and Local-aware Denoising Framework for Commonsense Knowledge Graph Noise Detection
Zheye Deng, Weiqi Wang, Zhaowei Wang +2
Commonsense Knowledge Graphs (CSKGs) are crucial for commonsense reasoning, yet constructing them through human annotations can be costly. As a result, various automatic methods ha…
QADYNAMICS: Training Dynamics-Driven Synthetic QA Diagnostic for Zero-Shot Commonsense Question Answering
Haochen Shi, Weiqi Wang, Tianqing Fang +4
Zero-shot commonsense Question-Answering (QA) requires models to reason about general situations beyond specific benchmarks. State-of-the-art approaches fine-tune language models o…
TILFA: A Unified Framework for Text, Image, and Layout Fusion in Argument Mining
Qing Zong, Zhaowei Wang, Baixuan Xu +6
A main goal of Argument Mining (AM) is to analyze an author's stance. Unlike previous AM datasets focusing only on text, the shared task at the 10th Workshop on Argument Mining int…
CAT: A Contextualized Conceptualization and Instantiation Framework for Commonsense Reasoning
Weiqi Wang, Tianqing Fang, Baixuan Xu +3
Commonsense reasoning, aiming at endowing machines with a human-like ability to make situational presumptions, is extremely challenging to generalize. For someone who barely knows…
COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspective
Zhaowei Wang, Quyet V. Do, Hongming Zhang +6
Detecting commonsense causal relations (causation) between events has long been an essential yet challenging task. Given that events are complicated, an event may have different ca…