2025
Understanding and Improving Information Preservation in Prompt Compression for LLMs
EMNLP 2025
Recent advancements in large language models (LLMs) have enabled their successful application to a broad range of tasks. However, in information-intensive tasks, the prompt length can grow fast, leading to increased computational requirements, performance degradation, and induced biases from irrelev