Runjin Chen

According to our database, Runjin Chen authored at least 18 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Persona Vectors: Monitoring and Controlling Character Traits in Language Models.

Runjin Chen, Andy Arditi, Henry Sleight, Owain Evans, Jack Lindsey

CoRR, July, 2025

Inverse Scaling in Test-Time Compute.

Aryo Pradipta Gema, Alexander Hägele, Runjin Chen, Andy Arditi, Jacob Goldman-Wetzler, Kit Fraser-Taliente, Henry Sleight, Linda Petrini, Julian Michael, Beatrice Alex, Pasquale Minervini, Yanda Chen, Joe Benton, Ethan Perez

CoRR, July, 2025

LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning.

Gabriel J. Perin, Runjin Chen, Xuxi Chen, Nina S. T. Hirata, Zhangyang Wang, Junyuan Hong

CoRR, June, 2025

Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning.

Ngoc Bui, Menglin Yang, Runjin Chen, Leonardo Neves, Mingxuan Ju, Rex Ying, Neil Shah, Tong Zhao

CoRR, June, 2025

VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction.

Zhiwen Fan, Jian Zhang, Renjie Li, Junge Zhang, Runjin Chen, Hezhen Hu, Kevin Wang, Huaizhi Qu, Dilin Wang, Zhicheng Yan, Hongyu Xu, Justin Theiss, Tianlong Chen, Jiachen Li, Zhengzhong Tu, Zhangyang Wang, Rakesh Ranjan

CoRR, May, 2025

SEAL: Steerable Reasoning Calibration of Large Language Models for Free.

Runjin Chen, Zhenyu Zhang, Junyuan Hong, Souvik Kundu, Zhangyang Wang

CoRR, April, 2025

More is Less: The Pitfalls of Multi-Model Synthetic Preference Data in DPO Safety Alignment.

Yifan Wang, Runjin Chen, Bolian Li, David Cho, Yihe Deng, Ruqi Zhang, Tianlong Chen, Zhangyang Wang, Ananth Grama, Junyuan Hong

CoRR, April, 2025

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems.

Xinyi Wu, Donald Loveland, Runjin Chen, Yozen Liu, Xin Chen, Leonardo Neves, Ali Jadbabaie, Mingxuan Ju, Neil Shah, Tong Zhao

Proceedings of the ACM on Web Conference 2025, 2025

Extracting and Understanding the Superficial Knowledge in Alignment.

Runjin Chen, Gabriel J. Perin, Xuxi Chen, Xilun Chen, Yan Han, Nina S. T. Hirata, Junyuan Hong, Bhavya Kailkhura

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

2024

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems.

Xinyi Wu, Donald Loveland, Runjin Chen, Yozen Liu, Xin Chen, Leonardo Neves, Ali Jadbabaie, Clark Mingxuan Ju, Neil Shah, Tong Zhao

CoRR, 2024

Enhancing Item Tokenization for Generative Recommendation through Self-Improvement.

Runjin Chen, Mingxuan Ju, Ngoc Bui, Dimosthenis Antypas, Stanley Cai, Xiaopeng Wu, Leonardo Neves, Zhangyang Wang, Neil Shah, Tong Zhao

CoRR, 2024

Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding.

Zhenyu Zhang, Runjin Chen, Shiwei Liu, Zhewei Yao, Olatunji Ruwase, Beidi Chen, Xiaoxia Wu, Zhangyang Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Q-Hitter: A Better Token Oracle for Efficient LLM Inference via Sparse-Quantized KV Cache.

Zhenyu Zhang, Shiwei Liu, Runjin Chen, Bhavya Kailkhura, Beidi Chen, Atlas Wang

Proceedings of the Seventh Annual Conference on Machine Learning and Systems, 2024

LLaGA: Large Language and Graph Assistant.

Runjin Chen, Tong Zhao, Ajay Kumar Jaiswal, Neil Shah, Zhangyang Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022

GCF-RD: A Graph-based Contrastive Framework for Semi-Supervised Learning on Relational Databases.

Runjin Chen, Tong Li, Yanyan Shen, Luyu Qiu, Kaidi Li, Caleb Chen Cao

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

GNEM: A Generic One-to-Set Neural Entity Matching Framework.

Runjin Chen, Yanyan Shen, Dongxiang Zhang

Proceedings of the WWW '21: The Web Conference 2021, 2021

2019

Towards a Deep and Unified Understanding of Deep Neural Models in NLP.

Chaoyu Guan, Xiting Wang, Quanshi Zhang, Runjin Chen, Di He, Xing Xie

Proceedings of the 36th International Conference on Machine Learning, 2019

Explaining Neural Networks Semantically and Quantitatively.

Runjin Chen, Hao Chen, Ge Huang, Jie Ren, Quanshi Zhang

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019