Papers by Mingming Yin

3 papers
Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention (P19-1)

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Challenge: Abstractive Sentence Summarization (ASSUM) is a monolingual task that focuses on grasping the core idea of the source sentence and presenting it as the summary.
Approach: They propose to use monolingual ASSUM to train a cross-lingual ASL system . they propose to train the system on summary word generation and attention .
Outcome: Experiments show that the proposed method improves on the monolingual ASSUM task.
Learning to Translate by Translating: Stabilizing the Dual Loop via Semantic-Aware Self-Evolution (2026.findings-acl)

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Challenge: Large Language Models (LLMs) have been successful in machine translation, but lack of high-quality parallel corpora and cost constrain scalability.
Approach: They propose an LLM-driven dual-learning framework that enables autonomous translation . they employ a robust semantic-aware reward function that balances adequacy with reconstruction fidelity .
Outcome: The proposed model outperforms larger models on benchmarks and achieves parity with state-of-the-art supervised baselines on mainstream benchmarks.
Contrastive Attention Mechanism for Abstractive Sentence Summarization (D19-1)

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Challenge: Existing attention mechanisms for abstractive sentence summarization are based on rule-based methods and large-scale training corpora.
Approach: They propose a contrastive attention mechanism that extends the sequence-to-sequence framework for abstractive sentence summarization task.
Outcome: The proposed mechanism improves the state-of-the-art on the abstractive sentence summarization task.

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