Please refer to table 1. The harmful keywords are with red and the unharmful keywords are withgreen background color.

Warning: This paper contains inappropriate/harmful visual contents. While widespread access to the Internet and the rapid advancement of generative models boost people's creativity and productivity, the risk of encountering inappropriate or harmful content also increases.

Nature and geometry furnish us with many such patterns, such as coastlines, snowflakes, the Cantor set and the Kuch curve.

We leverage this unique capability to propose NoMAD-Attention, an efficient attention algorithm that replaces MAD operations with in-register lookups.

The predominant de facto paradigm of testing ML models relies on either using only held-out data to compute aggregate evaluation metrics or by assessing the performance on different subgroups.

Figure 4: Our designed prompts without the Chain-of-Thought idea. Task 3(b) is for inquiries. Figure 5: Our designed prompts with the Chain-of-Thought idea. Task 3(b) is for inquiries. Thought prompts for Task 1 and Task 2 are presented in Figure 5. Scoring Objective For the LLMs' output response to each input cunning text, please refer to the Scoring Rules The scoring values are defined as {1, 2, 3, 4, 5}.

Inspired by the above motivation, we collect real cunning texts as our raw data from a famous Chinese online forum, the "Ruozhiba" (retard forum)

Compiler backends are tasked with generating executable machine code for processors. With the proliferation of diverse processors, it is imperative for programmers to tailor specific compiler backends to accommodate each one.