Papers by Yunpeng Qi

3 papers
Logical DA: Enhancing Data Augmentation for Logical Reasoning via a Multi-Agent System (2025.findings-acl)

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Challenge: Existing data augmentation paradigms isolate data synthesis from label validation, thereby reducing their utility for complex reasoning tasks.
Approach: They propose a framework for enhancing reasoning-focused data augmentation in few-shot learning scenarios that integrates four agents through two synergistic phases: diverse data generation and label verification.
Outcome: The proposed framework achieves the highest average improvement in task accuracy in both fine-tuning and in-context learning paradigms.
TALON: A Multi-Agent Framework for Long-Table Exploration and Question Answering (2025.emnlp-main)

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Challenge: Existing approaches to query-relevant content retrieval fail to retrieve contextually relevant data.
Approach: They propose a multi-agent framework for table question answering over long tables . TALON features a planning agent that iteratively invokes a tool agent to access tabular data .
Outcome: The proposed framework achieves average accuracy improvements of 7.5% and 12.0% across all language models.
LitVISTA: A Benchmark for Narrative Orchestration in Literary Text (2026.acl-long)

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Challenge: Existing large language models focus on causal coherence, neglecting the complex story arcs and orchestration inherent in human narratives.
Approach: They propose a high-dimensional framework for narrative orchestration that unifies human and model perspectives while jointly characterizing narrative function and structure in a common space.
Outcome: The proposed framework unifies human and model perspectives while jointly characterizing narrative function and structure in a common space.

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