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Jena Hwang

3 accepted papers

2024

Relying on the Unreliable: The Impact of Language Models’ Reluctance to Express Uncertainty

ACL 2024long

As natural language becomes the default interface for human-AI interaction, there is a need for LMs to appropriately communicate uncertainties in downstream applications. In this work, we investigate how LMs incorporate confidence in responses via natural language and how downstream users behave in…

Cited by 49SourcePDFScholar
2024

UNcommonsense Reasoning: Abductive Reasoning about Uncommon Situations

NAACL 2024long

Language technologies that accurately model the dynamics of events must perform commonsense reasoning. Existing work evaluating commonsense reasoning focuses on making inferences about common, everyday situations. To instead investigate the ability to model unusual, unexpected, and unlikely situatio…

Cited by 3SourcePDFScholar
2022

Symbolic Knowledge Distillation: from General Language Models to Commonsense Models

NAACL 2022long

The common practice for training commonsense models has gone from–human–to–corpus–to–machine: humans author commonsense knowledge graphs in order to train commonsense models. In this work, we investigate an alternative, from–machine–to–corpus–to–machine: general language models author these commonse…