Beyond Outcomes: Dual-View Relational Learning for Efficient Agent Benchmarking
This work proposes DualViewEval, an agent benchmark compression method that jointly exploits outcome and process relations to learn an exact-size miniset and predict the full-benchmark scores, and achieves the best results in all datasets.
Xin-Shuai Guo, Jun-Jie Wu, Dolly Deng et al.
· 0 citations