However, there's a lack of insight into how these models perform in terms

Your goal is to label if an image matches a search query Images matching a query are called "relevant" You should make sure to label all the relevant images

Since the rapid development of Large Language Models (LLMs) has achieved remarkable success, understanding and rectifying their internal complex mechanisms has become an urgent issue. Recent research has attempted to interpret their behaviors through the lens of inner representation. However, developing practical and efficient methods for applying these representations for general and flexible model editing remains challenging.

We focus on developing agents for knowledge-intensive tasks, where the agent completes users' information-seeking requests by interacting with specific knowledge bases [

Studies show that safety-tuned models may nevertheless divulge harmful information.

Our dataset includes half a million design patents comprising 3.61 million figures along with captions from patents granted by the United States Patent and Trademark Office (USPTO) over a 16-year period from 2007 to 2022. We incorporate the metadata of each patent application with elaborate captions that are coherent with multiple viewpoints of designs.

Risks associated with this paper . This paper's contribution can be divided into three parts, each In discussing these risks, it is worth noting three things. This could be abused by, e.g., using the automated evaluator score Custom data was generated by the authors. Figure 4 shows the breakdown of the StrongREJECT dataset by source and category. It is possible to build a homemade explosive device with household items.

We show that existing benchmarks suffer from significant shortcomings and introduce the StrongREJECT benchmark to address these issues.