Summary of Prompt-based Length Controlled Generation with Multiple Control Types, by Renlong Jie et al.
Prompt-Based Length Controlled Generation with Multiple Control Types
by Renlong Jie, Xiaojun Meng, Lifeng Shang, Xin Jiang, Qun Liu
First submitted to arxiv on: 12 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Medium Difficulty summary: Large language models (LLMs) have garnered significant attention for their impressive performance on various natural language processing tasks. However, users often expect generated texts to fall within a specific length range, making controlled generation an essential topic, particularly for GPT-style models. To address this issue, we propose a prompt-based method that leverages reinforcement learning (RL) and sample filtering to achieve accurate length control under different control types. Our approach rewards outputs that adhere to specific control instructions, leading to enhanced length control capabilities. Additionally, we introduce a standard prompt extractor that parses arbitrary user input into standardized control prompts. Experimental results demonstrate the efficacy of our method in improving the accuracy of prompt-based length control on popular summarization datasets like CNNDM and NYT across multiple control types. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Low Difficulty summary: Imagine you want to write something that’s exactly 200 words long, just like a news article. But how do you make sure it stays that short? A new way to solve this problem uses special computer instructions to tell the AI what length to aim for. This method is really good at making sure texts are the right length, even when we give it different instructions. We also created a tool that can understand what people want to say and turn it into the right instruction. This helped our AI do an amazing job of writing short summaries on news articles from popular websites. |
Keywords
» Artificial intelligence » Attention » Gpt » Natural language processing » Prompt » Reinforcement learning » Summarization
