Papers by Ijun Jang
Stable On-Policy Distillation through Adaptive Target Reformulation (2026.findings-acl)
Copied to clipboard
| Challenge: | Knowledge distillation (KD) is widely used for transferring capabilities from proprietary models to efficient open-source counterparts. |
| Approach: | They propose a method that constructs a geometric target distribution in logit space to emphasize agreement between the teacher and the student. |
| Outcome: | Experiments show that the proposed method outperforms supervised fine-tuning and existing on-policy baselines. |
Evaluating Structure-Aware Retrieval and Safety in Statute-Centric Legal QA (2026.acl-long)
Copied to clipboard
Kyubyung Chae, Jewon Yeom, Jeongjae Park, Seunghyun Bae, Ijun Jang, Hyunbin Jin, Jinkwan Jang, Taesup Kim
| Challenge: | Legal QA benchmarks focus on case law, overlooking statute-centric regulatory reasoning . relevant evidence is distributed across hierarchically linked documents, creating statutory retrieval gap . |
| Approach: | They propose a structure- and safety-aware benchmark for statute-centric legal QA . the benchmark assesses whether models can retrieve hierarchically fragmented evidence . |
| Outcome: | The proposed benchmark evaluates whether models can retrieve hierarchically fragmented evidence and safely abstain when statutory context is insufficient. |