Papers by Yichen Dong

3 papers
M2PO: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation (2026.acl-long)

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Challenge: prevailing methods for machine translation are often hindered by misleading reward signals.
Approach: They propose a framework that aligns large language models to human preferences . they propose 'M2PO' to correct the bias towards partial errors .
Outcome: The proposed framework outperforms open-source models and achieves parity with proprietary models.
Two Intermediate Translations Are Better Than One: Fine-tuning LLMs for Document-level Translation Refinement (2025.acl-long)

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Challenge: Recent research has shown that large language models (LLMs) can enhance translation quality through self-refinement.
Approach: They propose to extend translation refinement from sentence-level to document-level by using document-to-document (Doc2Doc) translations.
Outcome: The proposed method improves translation quality across ten translation tasks with LLaMA-3-8B-Instruct and Mistral-Nemo-Instru.
Graph Counselor: Adaptive Graph Exploration via Multi-Agent Synergy to Enhance LLM Reasoning (2025.acl-long)

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Challenge: Existing methods for enhancing LLM reliability suffer from inefficient information aggregation and rigid reasoning schemes.
Approach: They propose a method that explicitly models external knowledge integration capabilities by explicitly modeling knowledge relationships.
Outcome: The proposed method outperforms existing methods in multiple graph reasoning tasks.

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