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Found 4 papers, 1 papers with code
Distilling Structured Knowledge for Text-Based Relational Reasoning
There is an increasing interest in developing text-based relational reasoning systems, which are capable of systematically reasoning about the relationships between entities mentioned in a text.
Identifying and Analyzing Task-Encoding Tokens in Large Language Models
In-context learning (ICL) has become an effective solution for few-shot learning in natural language processing.
Learning Dynamic Belief Graphs to Generalize on Text-Based Games
Playing text-based games requires skills in processing natural language and sequential decision making.
Systematic Error Analysis of the Stanford Question Answering Dataset
This process also enabled us to identify the primary QA strategy learned by the models, i. e., systems determined the acceptable answer type for a question and then selected the acceptable answer span of that type containing the highest density of words present in the question within its local vicinity in the passage.
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