This paper wasn't for SKILLS per se, but for LLMs, and suggests that LLMs can't follow too many constraints at one time very well https://arxiv.org/abs/2608.12426 . Other papers suggest that LLMs show more information sparsity in the results with negative constraints.
Good one; reading this briefly took me back to the days of “Needle in a Haystack” being super challenging for LLMs. Maybe there needs to be a benchmark of “Rule in a Haystack” (similar to information one, testing not only independent rules also the ones that need hops) to clarify model performance regarding this. Thank you for the resource.
This paper wasn't for SKILLS per se, but for LLMs, and suggests that LLMs can't follow too many constraints at one time very well https://arxiv.org/abs/2608.12426 . Other papers suggest that LLMs show more information sparsity in the results with negative constraints.
Good one; reading this briefly took me back to the days of “Needle in a Haystack” being super challenging for LLMs. Maybe there needs to be a benchmark of “Rule in a Haystack” (similar to information one, testing not only independent rules also the ones that need hops) to clarify model performance regarding this. Thank you for the resource.