Papers by Boxiu Li

1 papers
SIFT: Grounding LLM Reasoning in Contexts via Stickers (2025.findings-emnlp)

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Challenge: Using a new approach, we can improve the pass@1 accuracy of LLM reasoning in large language models.
Approach: They propose a method that leverages increasing inference-time compute to ground LLM reasoning in contexts.
Outcome: The proposed approach improves pass@1 accuracy of DeepSeek-R1 on AIME2024 from 78.33% to **85.67%** and that on Aime2025 from 69.8% to **77.33%**.

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