9 citations · 34 across the 7 of their papers we have counts for
10 papers
Open-domain Question Answering via Chain of Reasoning over Heterogeneous Knowledge
Kaixin Ma, Hao Cheng, Xiaodong Liu +2
We propose a novel open-domain question answering (ODQA) framework for answering single/multi-hop questions across heterogeneous knowledge sources. The key novelty of our method is…
An Empirical Investigation of Commonsense Self-Supervision with Knowledge Graphs
Jiarui Zhang, Filip Ilievski, Kaixin Ma +2
Self-supervision based on the information extracted from large knowledge graphs has been shown to improve the generalization of language models, in zero-shot evaluation on various…
Generalizable Neuro-symbolic Systems for Commonsense Question Answering
Alessandro Oltramari, Jonathan Francis, Filip Ilievski +2
This chapter illustrates how suitable neuro-symbolic models for language understanding can enable domain generalizability and robustness in downstream tasks. Different methods for…
Exploring Strategies for Generalizable Commonsense Reasoning with Pre-trained Models
Kaixin Ma, Filip Ilievski, Jonathan Francis +3
Commonsense reasoning benchmarks have been largely solved by fine-tuning language models. The downside is that fine-tuning may cause models to overfit to task-specific data and the…
Dimensions of Commonsense Knowledge
Filip Ilievski, Alessandro Oltramari, Kaixin Ma +3
Commonsense knowledge is essential for many AI applications, including those in natural language processing, visual processing, and planning. Consequently, many sources that includ…
Lexically-constrained Text Generation through Commonsense Knowledge Extraction and Injection
Yikang Li, Pulkit Goel, Varsha Kuppur Rajendra +5
Conditional text generation has been a challenging task that is yet to see human-level performance from state-of-the-art models. In this work, we specifically focus on the Commonge…