Papers by Chien-Ming Huang
Mapping Smarter, Not Harder: A Test-Time Reinforcement Learning Agent That Improve Without Labels or Model Updates (2025.emnlp-industry)
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| Challenge: | a new agent that can improve schema mappings for third-party logs is needed for enterprise intelligence platforms. |
| Approach: | They propose a reinforcement learning agent that can self-improve without labeled examples or model weight updates. |
| Outcome: | The proposed method increases mapping accuracy from 56.4% (LLM-only) to 72.73% (RAG) to 93.94% over 100 iterations using GPT-4o. |
Primus: A Pioneering Collection of Open-Source Datasets for Cybersecurity LLM Training (2025.emnlp-main)
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| Challenge: | Large Language Models (LLMs) have shown remarkable advancements in specialized fields such as finance, law, and medicine. |
| Approach: | They propose to provide datasets covering all major training stages including pretraining, instruction fine-tuning, and reasoning distillation with cybersecurity-specific self-reflection data. |
| Outcome: | Extensive ablation studies show that LLMs acquire their knowledge during pretraining, while reasoning distillation leads to a 15% gain in security certification (CISSP). |