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cs.CL2024
Dynamic Multi-Reward Weighting for Multi-Style Controllable Generation
Karin de Langis, Ryan Koo, Dongyeop Kang
Textual style expresses a diverse set of information, including interpersonal dynamics (e.g., formality) and the author's emotions or attitudes (e.g., disgust). An open question is…
cs.CL2024★ 2 cited
Under the Surface: Tracking the Artifactuality of LLM-Generated Data
Debarati Das, Karin De Langis, Anna Martin-Boyle +14
This work delves into the expanding role of large language models (LLMs) in generating artificial data. LLMs are increasingly employed to create a variety of outputs, including ann…