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Found 4 papers, 2 papers with code
Generating Situated Reflection Triggers about Alternative Solution Paths: A Case Study of Generative AI for Computer-Supported Collaborative Learning
An advantage of Large Language Models (LLMs) is their contextualization capability - providing different responses based on student inputs like solution strategy or prior discussion, to potentially better engage students than standard feedback.
Do LLMs exhibit human-like response biases? A case study in survey design
As large language models (LLMs) become more capable, there is growing excitement about the possibility of using LLMs as proxies for humans in real-world tasks where subjective labels are desired, such as in surveys and opinion polling.
Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong
To reduce over-reliance on LLMs, we ask LLMs to provide contrastive information - explain both why the claim is true and false, and then we present both sides of the explanation to users.
"Merge Conflicts!" Exploring the Impacts of External Distractors to Parametric Knowledge Graphs
Large language models (LLMs) acquire extensive knowledge during pre-training, known as their parametric knowledge.
