1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.SE2025
Benchmarking Failures in Tool-Augmented Language Models
Eduardo Treviño, Hugo Contant, James Ngai +2
The integration of tools has extended the capabilities of language models (LMs) beyond vanilla text generation to versatile scenarios. However, tool-augmented language models (TaLM…
cs.LG2025★ 1 cited
The MASK Benchmark: Disentangling Honesty From Accuracy in AI Systems
Richard Ren, Arunim Agarwal, Mantas Mazeika +13
As large language models (LLMs) become more capable and agentic, the requirement for trust in their outputs grows significantly, yet at the same time concerns have been mounting th…