Papers with retaining accuracy

2 papers
Keep It Simple: Unsupervised Simplification of Multi-Paragraph Text (2021.acl-long)

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Challenge: a novel approach to text simplification learns to balance a reward across three properties: fluency, salience and simplicity.
Approach: They propose a novel algorithm to optimize the reward which proposes several candidate simplifications and a realistic text comprehension task as an evaluation method for text simplification.
Outcome: The proposed model outperforms strong supervised baselines on the English news domain and can help people complete a comprehension task an average of 18% faster while retaining accuracy.
MiniKV: Pushing the Limits of 2-Bit KV Cache via Compression and System Co-Design for Efficient Long Context Inference (2025.findings-acl)

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Challenge: State-of-the-art 2-bit KV cache quantization methods achieve excellent results in accelerating LLM inference while retaining accuracy on long context tasks.
Approach: They propose a method based on 2-bit KV cache quantization with adaptive KV policies that retain LLM accuracy with only a subset of KV states.
Outcome: The proposed method outperforms state-of-the-art methods on a wide range of long context tasks while retaining accuracy.

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