VLM-RobustBench: A Comprehensive Benchmark for Robustness of Vision-Language Models
Rohit Saxena · Alessandro Suglia · Pasquale Minervini
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Rohit Saxena · Alessandro Suglia · Pasquale Minervini
Andreas Grivas · Lorenzo Loconte · Emile van Krieken · Piotr Nawrot · Yu Zhao · Euan Wielewski · Pasquale Minervini · Edoardo Ponti · Antonio Vergari
Yu Zhao · Wei-Ning Chen · Huseyin Inan · Samuel Kessler · Lu Wang · Lukas Wutschitz · Fangkai Yang · Chaoyun Zhang · Pasquale Minervini · Saravanakumar Rajmohan · Robert A Sim
Joshua Ong Jun Leang · Zheng Zhao · Aryo Pradipta Gema · Sohee Yang · Wai-Chung Kwan · Xuanli He · Wenda Li · Pasquale Minervini · Eleonora Giunchiglia · Shay B Cohen
Best-of- n sampling improves the accuracy of large language models (LLMs) and large reasoning models (LRMs) by generating multiple candidate solutions and selecting the one with the highest reward. The key challenge for reasoning tasks is designing a scoring function that can identify correct rea...