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Found 6 papers, 5 papers with code
Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark
And how do we measure these behaviors in general-purpose models such as GPT-4?
Improving Code Generation by Training with Natural Language Feedback
The potential for pre-trained large language models (LLMs) to use natural language feedback at inference time has been an exciting recent development.
Training Language Models with Language Feedback at Scale
Third, finetuning the language model to maximize the likelihood of the chosen refinement given the input.
How Would The Viewer Feel? Estimating Wellbeing From Video Scenarios
In experiments, we show how video models that are primarily trained to recognize actions and find contours of objects can be repurposed to understand human preferences and the emotional content of videos.
Few-shot Adaptation Works with UnpredicTable Data
Finetuning on the resulting dataset leads to improved FSL performance on Natural Language Processing (NLP) tasks, but not proportionally to dataset scale.
Training Language Models with Language Feedback
We learn from language feedback on model outputs using a three-step learning algorithm.
