Papers by Canming Huang

3 papers
Exploring the Capacity of Pretrained Language Models for Reasoning about Actions and Change (2023.acl-long)

Copied to clipboard

Challenge: Recent transformer-based language models (LMs) provide reasoning over textual benchmarks . RAC is essential to understand and interact with the ever-changing environment .
Approach: They propose to use a transformer-based language model to learn to reason over textual benchmarks.
Outcome: The proposed model minimizes the influence of other linguistic requirements to focus on RAC.
WinoLogic: A Zero-Shot Logic-based Diagnostic Dataset for Winograd Schema Challenge (2021.emnlp-main)

Copied to clipboard

Challenge: Recent success of neural language models on the Winograd Schema Challenge has called for further investigation of commonsense reasoning ability of these models.
Approach: They propose a logic-based framework that focuses on high-quality commonsense knowledge.
Outcome: The proposed framework focuses on high-quality commonsense knowledge.
Improving Unsupervised Commonsense Reasoning Using Knowledge-Enabled Natural Language Inference (2021.findings-emnlp)

Copied to clipboard

Challenge: Recent methods based on pre-trained language models have shown strong supervised performance on commonsense reasoning.
Approach: They propose to use a common framework to solve commonsense reasoning tasks using a dataset from NLI.
Outcome: The proposed method achieves state-of-the-art unsupervised performance on two commonsense reasoning tasks.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations