Papers by Zijian Xie

2 papers
Evidence-Augmented Policy Optimization with Reward Co-Evolution for Long-Context Reasoning (2026.acl-long)

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Challenge: Evidence-Augmented Policy Optimization (EAPO) improves long-context reasoning performance . Xu et al., 2025): large language models are a critical part of NLP .
Approach: They propose an Evidence-Augmented Reasoning paradigm that uses a group-relative reward to improve evidence quality.
Outcome: EAPO significantly improves long-context reasoning performance compared to baselines.
LLEOT: A Privacy-Enhancing Offsite Tuning Framework via Loss Landscape Elevation (2026.findings-acl)

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Challenge: Existing approaches to fine-tune large language models are infeasible due to privacy regulations.
Approach: They propose an offsite tuning framework that secures data privacy and model parameter and capability privacy.
Outcome: The proposed framework secures data privacy and model parameter and capability privacy while preserving gradient alignment.

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