Papers by Cailian Chen
RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents (2026.acl-long)
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Jize Wang, Han Wu, Zhiyuan You, Yiming Song, Yijun Wang, Zifei Shan, Yining Li, Songyang Zhang, Xinyi Le, Cailian Chen, Xinping Guan, Dacheng Tao
| Challenge: | Existing methods for mixing-of-agents (MoA) lack model selection criteria and struggle with large model pools. |
| Approach: | They propose a mixture-of-agents framework with dynamic routing that uses a lightweight scorer to perform initial screening and refines the model scores through self- and cross-assessment. |
| Outcome: | The proposed framework outperforms existing methods for large model pools and tasks . it reduces cost by 89.8% and latency by 63.6% in the large-scale model pool. |
Adaptive Hinge Balance Loss for Document-Level Relation Extraction (2023.findings-emnlp)
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| Challenge: | Document-Level Relation Extraction is a multi-label classification task . however, most entity pairs do not express any relations . |
| Approach: | They propose to use a distance between the classification threshold and predicted score to reduce the imbalance problem by balancing the easy negatives. |
| Outcome: | The proposed method is superior to other methods, the authors show . it reduces the threshold to an appropriate value, and increases quadratically with the number of entities. |