Seong Joon Oh

LLM agents struggle to translate general capabilities into cost-efficient, reusable solutions, often failing to outperform simple distillation baselines despite significant zero-shot prowess.

It is demonstrated that gradient-based attribution methods track format similarity more than task semantics, meaning that such methods, as well as the semantic interpretation of the gradient, should be tested on data where answer format and task vary independently for greater robustness and reliability.