Papers by Yawen Zeng
A Reasoner for Real-World Event Detection: Scaling Reinforcement Learning via Adaptive Perplexity-Aware Sampling Strategy (2025.emnlp-industry)
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| Challenge: | Existing methods for abnormal event detection face two predominant limitations . existing methods rely on specialized small models and are limited by performance bottlenecks . |
| Approach: | They propose a framework that leverages the advanced reasoning capabilities of large language models for abnormal event detection. |
| Outcome: | The proposed framework achieves the highest F1 score and an average improvement of 9.59% in OOD transfer tests. |
Distill The Image to Nowhere: Inversion Knowledge Distillation for Multimodal Machine Translation (2022.emnlp-main)
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| Challenge: | Existing studies on multimodal machine translation (MMT) have focused on the fusion and alignment of images and texts to improve MMT. |
| Approach: | They propose an image-free inference framework that supports image-based inference via an inversion knowledge distillation scheme. |
| Outcome: | The proposed framework is the first to rival or surpass image-must frameworks on the multimodal translation benchmark. |
When to Continue Thinking: Adaptive Thinking Mode Switching for Efficient Reasoning (2025.findings-emnlp)
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Xiaoyun Zhang, Jingqing Ruan, Xing Ma, Yawen Zhu, Haodong Zhao, Hao Li, Jiansong Chen, Ke Zeng, Xunliang Cai
| Challenge: | Large reasoning models (LRMs) incur excessive computational overhead due to redundant reasoning, especially on simple tasks. |
| Approach: | They propose an Adaptive Self-Recovery Reasoning framework that suppresses unnecessary reasoning and enables implicit recovery. |
| Outcome: | The proposed framework suppresses unnecessary reasoning and enables implicit recovery. |
QuantAgents: Towards Multi-agent Financial System via Simulated Trading (2025.findings-emnlp)
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| Challenge: | Existing LLM-based agent models exhibit significant deviations from real-world fund companies. |
| Approach: | They propose a multi-agent financial system that incorporates simulated trading . they propose simulated trades are evaluated without assuming actual risks . |
| Outcome: | The proposed system evaluates various investment strategies without assuming actual risks without involving real-world investors. |
HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs (2026.findings-acl)
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Ru Peng, Tianyu Zhao, Xijun Gu, Zhiting Fan, Haokai Xu, Jinyang Zhang, Yawen Zeng, Yihong Zhuang, Kexin Yang, Junyang Lin, Dayiheng Liu, Junbo Zhao
| Challenge: | High-quality, diverse data are vital for large language models (LLMs) but remain scarce and costly. |
| Approach: | They define the first HSS domain system covering 14 mainstream fields and introduce HSS-Synth. |
| Outcome: | the proposed pipeline outperforms 14 leading baselines on 16 benchmarks. |