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Found 7 papers, 3 papers with code
ERNIE-NLI: Analyzing the Impact of Domain-Specific External Knowledge on Enhanced Representations for NLI
We examine the effect of domain-specific external knowledge variations on deep large scale language model performance.
Analyzing the Limits of Self-Supervision in Handling Bias in Language
We define three broad classes of task descriptions for these tasks: statement, question, and completion, with numerous lexical variants within each class.
Disentangling Online Chats with DAG-Structured LSTMs
In this paper, we apply DAG-LSTMs to the conversation disentanglement task.
Identify, Align, and Integrate: Matching Knowledge Graphs to Commonsense Reasoning Tasks
For knowledge integration to yield peak performance, it is critical to select a knowledge graph (KG) that is well-aligned with the given task's objective.
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning
Recent commonsense-reasoning tasks are typically discriminative in nature, where a model answers a multiple-choice question for a certain context.
Simple Compounded-Label Training for Fact Extraction and Verification
Automatic fact checking is an important task motivated by the need for detecting and preventing the spread of misinformation across the web.
Commonsense for Generative Multi-Hop Question Answering Tasks
We instead focus on a more challenging multi-hop generative task (NarrativeQA), which requires the model to reason, gather, and synthesize disjoint pieces of information within the context to generate an answer.
Ranked #6 on
Question Answering
on NarrativeQA
