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Found 4 papers, 1 papers with code
Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences
In particular, we identify a phenomenon we dub \emph{criteria drift}: users need criteria to grade outputs, but grading outputs helps users define criteria.
Antagonistic AI
The vast majority of discourse around AI development assumes that subservient, "moral" models aligned with "human values" are universally beneficial -- in short, that good AI is sycophantic AI.
Imagining a Future of Designing with AI: Dynamic Grounding, Constructive Negotiation, and Sustainable Motivation
We ideate a future design workflow that involves AI technology.
ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing
Evaluating outputs of large language models (LLMs) is challenging, requiring making -- and making sense of -- many responses.
