Papers by Baoyun Peng
EffiQA: Efficient Question-Answering with Strategic Multi-Model Collaboration on Knowledge Graphs (2025.coling-main)
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Zixuan Dong, Baoyun Peng, Yufei Wang, Jia Fu, Xiaodong Wang, Xin Zhou, Yongxue Shan, Kangchen Zhu, Weiguo Chen
| Challenge: | Existing approaches that integrate LLMs and KGs either underutilize the reasoning abilities of LLM or suffer from prohibitive computational costs due to tight coupling. |
| Approach: | They propose a framework that can strike a balance between performance and efficiency via an iterative paradigm. |
| Outcome: | The proposed framework can strike a balance between performance and efficiency via an iterative paradigm. |
JI2S: Joint Influence‐Aware Instruction Data Selection for Efficient Fine‐Tuning (2025.emnlp-main)
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| Challenge: | Prior selection strategies score samples using generalpurpose LLMs, leveraging their strong language understanding but introducing inherent biases that misalign with the target model’s behavior and yield unstable downstream performance. |
| Approach: | They propose a framework that jointly models marginal and combinatorial influences within sample groups and evaluate them on Open LLM Benchmarks, MTBench, and GPT4–judged pairwise comparisons. |
| Outcome: | The proposed framework outperforms fulldataset training and strong baselines on Open LLM Benchmarks, MTBench, and GPT4–judged pairwise comparisons. |