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Found 12 papers, 6 papers with code
Implicit Chain of Thought Reasoning via Knowledge Distillation
In this work, we explore an alternative reasoning approach: instead of explicitly producing the chain of thought reasoning steps, we use the language model's internal hidden states to perform implicit reasoning.
Guiding Transformers to Process in Steps
Specifically, while learning a direct mapping from inputs to outputs is feasible for System 1 tasks, we argue that algorithmic System 2 tasks can only be solved by learning a mapping from inputs to outputs through a series of intermediate steps.
Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models
Targeted syntactic evaluations have demonstrated the ability of language models to perform subject-verb agreement given difficult contexts.
Investigating Gender Bias in Language Models Using Causal Mediation Analysis
As a case study, we apply this methodology to analyzing gender bias in pre-trained Transformer language models.
Probing Neural Dialog Models for Conversational Understanding
The predominant approach to open-domain dialog generation relies on end-to-end training of neural models on chat datasets.
Linguistic Features for Readability Assessment
Readability assessment aims to automatically classify text by the level appropriate for learning readers.
Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias
Common methods for interpreting neural models in natural language processing typically examine either their structure or their behavior, but not both.
Eliciting and Annotating Uncertainty in Spoken Language
In such applications, we would like to know the speaker{'}s actual level of certainty, but past research has only revealed listeners{'} perception of the speaker{'}s level of certainty.
