3 papers
cs.CL2024
Does Writing with Language Models Reduce Content Diversity?
Vishakh Padmakumar, He He
Large language models (LLMs) have led to a surge in collaborative writing with model assistance. As different users incorporate suggestions from the same model, there is a risk of…
cs.CL2024
Leveraging Implicit Feedback from Deployment Data in Dialogue
Richard Yuanzhe Pang, Stephen Roller, Kyunghyun Cho +2
We study improving social conversational agents by learning from natural dialogue between users and a deployed model, without extra annotations. To implicitly measure the quality o…
cs.CL2024
On the Relation between Sensitivity and Accuracy in In-context Learning
Yanda Chen, Chen Zhao, Zhou Yu +2
In-context learning (ICL) suffers from oversensitivity to the prompt, making it unreliable in real-world scenarios. We study the sensitivity of ICL with respect to multiple perturb…