Papers by Bojun Jin
A Multi-persona Framework for Argument Quality Assessment (2025.acl-long)
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| Challenge: | Existing methods for argument quality assessment do not consider multi-perspective evaluation due to subjective nature of arguments. |
| Approach: | They propose a multi-persona framework for argument quality assessment that simulates diverse evaluator perspectives through large language models. |
| Outcome: | The proposed framework outperforms baselines while providing comprehensive multi-perspective rationales on IBM-Rank-30k and IBM-ArgQ-5.3kArgs datasets. |
Exploring Quality and Diversity in Synthetic Data Generation for Argument Mining (2025.emnlp-main)
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| Challenge: | Argument Mining (AM) is hindered by the scarcity of structure-annotated datasets, which are expensive to create manually. |
| Approach: | They propose to use quality-oriented synthesis and diversity-oriented approach to generate argumentative texts with diverse topics and argument structures. |
| Outcome: | The proposed approach significantly improves existing models in full-data and low-resource settings. |
ArgGenBench: Benchmarking the Complex Controlled Argument Generation Capability of Large Language Models (2026.acl-long)
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| Challenge: | Existing studies focus on limited control signals such as topic, stance, length, style, strategy, audience, and key aspects, failing to capture this complexity. |
| Approach: | They propose a benchmark that integrates multi-dimensional control into a single instruction to evaluate LLMs' ability to produce persuasive arguments. |
| Outcome: | The proposed benchmarks show that existing models fail to capture multifaceted argumentative control signals. |