In this work, we propose a novel calibration method that can be used to combat hallucinations.

We bear all responsibility in case of violation of rights, etc., and confirmation of the data license. This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International This license permits sharing and adapting the work provided it is not used for commercial purposes and appropriate credit is given. Please refer to Section 3 for our hosting plan. In this section, we use the framework of Datasheets for Datasets [? ] to form a datasheet for CRAG, For what purpose was the dataset created? Was there a specific task in mind?

Compared to works that bake shading in the 3D object's appearance,

Generating natural and meaningful responses to communicate with multi-modal human inputs is a fundamental capability of Large Vision-Language Models (L VLMs).

We study the interplay between local differential privacy (LDP) and robustness to Huber corruption and possibly heavy-tailed rewards in the context of multi-armed bandits (MABs). We consider two different practical settings: LDP-then-Corruption (L TC) where each user's locally private response might be further corrupted during the data collection process, and Corruption-then-LDP (CTL)

Powered by remarkable advancements in Large Language Models (LLMs), Mul-timodal Large Language Models (MLLMs) demonstrate impressive capabilities in manifold tasks.

Alignment method inspired by an analogy with the concept of backdoor attacks. In particular, service providers will construct prefixed safety examples with a secret prompt, acting as a "backdoor trigger".