@article{jin2026shellelastic,title={{ShellElastic}: Scalable Elastic Pretraining with Simultaneous Maximal Updates and Hyperparameter Transfer},author={Jin, Can and Kang, Yan and Gong, Yifan and Ge, Chongjian and Xu, Mingze and Xiong, Yuanjun and Metaxas, Dimitris N. and Peng, Hongwu},journal={arXiv preprint arXiv:2610.15124},year={2026},note={Submitted to ICLR 2027},url={https://arxiv.org/abs/2610.15124},}
@inproceedings{yang2026act,title={Act More, Decide Less: Skill-Guided Adaptive Action Chunking for Long-Horizon LLM Agents},author={Yang, Yanting and Jin, Can and Zhao, Jinman and Wu, Jiahao and Zhou, Yang and Wang, Zhepeng and Wang, Zhendong and Zhou, Mu and Metaxas, Dimitris N.},booktitle={Findings of the Association for Computational Linguistics: EMNLP 2026},year={2026},url={https://arxiv.org/abs/2609.02042},}
@misc{zhou2026dare,title={DARE: Difficulty-Adaptive Reinforcement Learning with Co-Evolved Difficulty Estimation},author={Zhou, Yang and Jin, Can and Dong, Zihan and Wang, Zhepeng and Yang, Yanting and Zhao, Shiyu and Li, Lei and Bao, Runxue and Xie, Yaochen and Metaxas, Dimitris N.},year={2026},journal={arXiv preprint arXiv:2605.09188},}
@inproceedings{jin2026weak,title={Weak Critics Make Strong Learners: On-Policy Critique Distillation for Scalable Oversight},author={Jin, Can and Li, Jiakang and Wu, Rui and Zhang, Eddy Z. and Metaxas, Dimitris N.},booktitle={3rd AI for Math Workshop: Toward Self-Evolving Scientific Agents},year={2026},url={https://openreview.net/forum?id=oEfedgUChS},}
@inproceedings{jin2025dtopp,title={DTop-p MoE: Sparsity-Controlled Dynamic Top-p MoE for Foundation Model Pre-training},author={Jin, Can and Peng, Hongwu and Xiang, Mingcan and Zhang, Qixin and Yuan, Xiangchi and Hasan, Amit and Dibua, Ohiremen and Gong, Yifan and Kang, Yan and Metaxas, Dimitris N.},booktitle={Forty-third International Conference on Machine Learning},year={2026},}
@inproceedings{jin2026reasoning,title={Reasoning over Precedents Alongside Statutes: Case-Augmented Deliberative Alignment for LLM Safety},author={Jin, Can and Wu, Rui and Che, Tong and Zhang, Qixin and Peng, Hongwu and Zhao, Jiahui and Wang, Zhenting and Wei, Wenqi and Han, Ligong and Zhang, Zhao and Cao, Yuan and Tang, Ruixiang and Metaxas, Dimitris N.},booktitle={The 64th Annual Meeting of the Association for Computational Linguistics},year={2026},}
@inproceedings{jin2025two,title={Two Heads are Better Than One: Test-time Scaling of Multi-agent Collaborative Reasoning},author={Jin, Can and Peng, Hongwu and Zhang, Qixin and Zhou, Yang and Tang, Yujin and Che, Tong and Metaxas, Dimitris N.},booktitle={Findings of the Association for Computational Linguistics: EMNLP 2026},year={2026},url={https://arxiv.org/abs/2504.09772},}
@inproceedings{li2026latent,title={Latent Reward Steering: An Adaptive Inference-Time Framework that Implicitly Promotes Cognitive Behaviors in Reasoning LLMs},author={Li, Jiakang and Zhu, Guanyu and Jin, Can and Huang, Chenxi and Yu, Dexu and Chen, Ronghao and Zhou, Yang and Peng, Hongwu and Lan, Xuanqi and Metaxas, Dimitris N. and Li, Youhua},booktitle={Findings of the Association for Computational Linguistics: EMNLP 2026},year={2026},url={https://arxiv.org/abs/2606.00726},}
@inproceedings{sun2026uncertainty,title={Uncertainty-Aware Knowledge Distillation for Multimodal Large Language Models},author={Sun, Jingchen and Han, Shaobo and Patel, Deep and Kohno, Wataru and Jin, Can and Chen, Changyou},booktitle={The IEEE/CVF Conference on Computer Vision and Pattern Recognition},year={2026},}
@inproceedings{dong2026evaluating,title={Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals},author={Dong, Zihan and Zhang, Zhixian and Zhou, Yang and Jin, Can and Wu, Ruijia and Zhang, Linjun},booktitle={Forty-third International Conference on Machine Learning},year={2026},}
@inproceedings{zhou2025led,title={Led: Llm enhanced open-vocabulary object detection without human curated data generation},author={Zhou, Yang and Zhao, Shiyu and Chen, Yuxiao and Wang, Zhenting and Jin, Can and Metaxas, Dimitris N},booktitle={The IEEE/CVF Conference on Computer Vision and Pattern Recognition Findings},year={2026},}
@inproceedings{jin2025lorvp,title={LoR-{VP}: Low-Rank Visual Prompting for Efficient Vision Model Adaptation},author={Jin, Can and Li, Ying and Zhao, Mingyu and Zhao, Shiyu and Wang, Zhenting and He, Xiaoxiao and Han, Ligong and Che, Tong and Metaxas, Dimitris N.},booktitle={The Thirteenth International Conference on Learning Representations},year={2025},url={https://openreview.net/forum?id=5btFIv2PNb},}
@inproceedings{jin2025visual,title={Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective},author={Jin, Can and Huang, Tianjin and Zhang, Yihua and Pechenizkiy, Mykola and Liu, Sijia and Liu, Shiwei and Chen, Tianlong},booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},volume={39},number={4},pages={4111--4119},year={2025},url={https://arxiv.org/pdf/2312.01397},}
@inproceedings{jin2025apeer,title={APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking (<span class="award">Best Paper Award @ RelWeb</span>)},author={Jin, Can and Peng, Hongwu and Zhao, Shiyu and Wang, Zhenting and Xu, Wujiang and Han, Ligong and Zhao, Jiahui and Zhong, Kai and Rajasekaran, Sanguthevar and Metaxas, Dimitris N},booktitle={Companion Proceedings of the ACM Web Conference 2025},location={Sydney, NSW, Australia},series={WWW '25},year={2025},doi={10.1145/3701716.3717574},isbn={979-8-4007-1331-6/2025/04},url={https://arxiv.org/abs/2406.14449},publisher={Association for Computing Machinery},address={New York, NY, USA},keywords={Prompt engineering, Information Retrieval, Large Language Model, ReRanking},}
@inproceedings{liu2025graph,author={Liu, Libin and Chen, Shen and Jia, Sen and Shi, Jingzhe and Jin, Can and Wu, Zongkai and Hwang, Jenq-Neng and Li, Lei},title={Graph Canvas for Controllable 3D Scene Generation},year={2025},isbn={9798400720352},publisher={Association for Computing Machinery},address={New York, NY, USA},url={https://doi.org/10.1145/3746027.3754554},doi={10.1145/3746027.3754554},booktitle={Proceedings of the 33rd ACM International Conference on Multimedia},pages={2536–2545},numpages={10},keywords={3d generation, graph representation, multimodal large language model, spatial intelligence},location={Dublin, Ireland},series={MM '25},}
@inproceedings{zhang2025effective,title={Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives},author={Zhang, Qixin and Sun, Yan and Jin, Can and ZHANG, Xikun and Shu, Yao and Zhao, Puning and Shen, Li and Tao, Dacheng},booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems},year={2025},url={https://openreview.net/forum?id=isAYKdLwtB},}
@inproceedings{zhang2025multinoulli,title={Multinoulli Extension: A Lossless Yet Effective Probabilistic Framework for Subset Selection over Partition Constraints},author={Zhang, Qixin and Huang, Wei and Jin, Can and Zhao, Puning and Shu, Yao and Shen, Li and Tao, Dacheng},booktitle={Forty-second International Conference on Machine Learning},year={2025},url={https://openreview.net/forum?id=6XQOarhYF8},}
@inproceedings{jin2024lot,author={Jin, Can and Che, Tong and Peng, Hongwu and Li, Yiyuan and Metaxas, Dimitris and Pavone, Marco},booktitle={Advances in Neural Information Processing Systems},editor={Globerson, A. and Mackey, L. and Belgrave, D. and Fan, A. and Paquet, U. and Tomczak, J. and Zhang, C.},pages={966--994},publisher={Curran Associates, Inc.},title={Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate},url={https://proceedings.neurips.cc/paper_files/paper/2024/file/01ce1ae7f94d139e4917f9e4425a4f38-Paper-Conference.pdf},volume={37},year={2024},}
