238 citations · 268 across the 11 of their papers we have counts for
11 papers · 1 filter
Synergizing Large Language Models and Theory for Human-like Causal Reasoning
Yanxi Zhang, Xin Cong, Zhong Zhang +3
Performing causal reasoning akin to humans is fundamental to achieving strong artificial intelligence. However, existing studies on causal reasoning and large language models (LLMs…
CASA: Causality-driven Argument Sufficiency Assessment
Xiao Liu, Yansong Feng, Kai-Wei Chang
The argument sufficiency assessment task aims to determine if the premises of a given argument support its conclusion. To tackle this task, existing works often train a classifier…
How Many Answers Should I Give? An Empirical Study of Multi-Answer Reading Comprehension
Chen Zhang, Jiuheng Lin, Xiao Liu +3
The multi-answer phenomenon, where a question may have multiple answers scattered in the document, can be well handled by humans but is challenging enough for machine reading compr…
The Magic of IF: Investigating Causal Reasoning Abilities in Large Language Models of Code
Xiao Liu, Da Yin, Chen Zhang +2
Causal reasoning, the ability to identify cause-and-effect relationship, is crucial in human thinking. Although large language models (LLMs) succeed in many NLP tasks, it is still…
Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation
Da Yin, Xiao Liu, Fan Yin +4
Instruction tuning has emerged to enhance the capabilities of large language models (LLMs) to comprehend instructions and generate appropriate responses. Existing methods either ma…
Counterfactual Recipe Generation: Exploring Compositional Generalization in a Realistic Scenario
Xiao Liu, Yansong Feng, Jizhi Tang +2
People can acquire knowledge in an unsupervised manner by reading, and compose the knowledge to make novel combinations. In this paper, we investigate whether pretrained language m…
Things not Written in Text: Exploring Spatial Commonsense from Visual Signals
Xiao Liu, Da Yin, Yansong Feng +1
Spatial commonsense, the knowledge about spatial position and relationship between objects (like the relative size of a lion and a girl, and the position of a boy relative to a bic…
Everything Has a Cause: Leveraging Causal Inference in Legal Text Analysis
Xiao Liu, Da Yin, Yansong Feng +2
Causal inference is the process of capturing cause-effect relationship among variables. Most existing works focus on dealing with structured data, while mining causal relationship…
Neighborhood Matching Network for Entity Alignment
Yuting Wu, Xiao Liu, Yansong Feng +2
Structural heterogeneity between knowledge graphs is an outstanding challenge for entity alignment. This paper presents Neighborhood Matching Network (NMN), a novel entity alignmen…
Jointly Learning Entity and Relation Representations for Entity Alignment
Yuting Wu, Xiao Liu, Yansong Feng +2
Entity alignment is a viable means for integrating heterogeneous knowledge among different knowledge graphs (KGs). Recent developments in the field often take an embedding-based ap…
Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs
Yuting Wu, Xiao Liu, Yansong Feng +3
Entity alignment is the task of linking entities with the same real-world identity from different knowledge graphs (KGs), which has been recently dominated by embedding-based metho…