Summary of Cannot or Should Not? Automatic Analysis Of Refusal Composition in Ift/rlhf Datasets and Refusal Behavior Of Black-box Llms, by Alexander Von Recum et al.
Cannot or Should Not? Automatic Analysis of Refusal Composition in IFT/RLHF Datasets and Refusal Behavior of Black-Box LLMs
by Alexander von Recum, Christoph Schnabl, Gabor Hollbeck, Silas Alberti, Philip Blinde, Marvin von Hagen
First submitted to arxiv on: 22 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper investigates the crucial phenomenon of “refusals” in large language models (LLMs), where these AI systems decline or fail to fully execute user instructions. Specifically, it highlights the importance of refusals in both AI safety and capabilities, particularly in reducing hallucinations. The authors show that these behaviors are learned during post-training, especially through instruction fine-tuning (IFT) and reinforcement learning from human feedback (RLHF). However, existing taxonomies and evaluation datasets for refusals are inadequate, often focusing solely on should-not-related categories and lacking tools for auditing refusal content in black-box LLM outputs. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about how AI language models sometimes say “no” to user requests. It’s important because it can help make AI safer and more helpful. The researchers found that these “refusals” are learned by the AI systems during training, especially when they’re taught what to do or not do through feedback from humans. But right now, there aren’t good ways to classify or test these refusals, which makes it hard to understand how AI is working. |
Keywords
» Artificial intelligence » Fine tuning » Reinforcement learning from human feedback » Rlhf
