Runjin Chen

27 papers A* 8A 1Journal 16Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Neurosymbolic LoRA: Why and When to Tune Weights vs. Rewrite Prompts.
CoRR
Kevin Wang, Neel P. Bhatt, Cong Liu, Junbo Li, Runjin Chen, Yihan Xi, Timothy Barclay, Alvaro Velasquez, Ufuk Topcu, Zhangyang Wang
2025 — conf
Extracting and Understanding the Superficial Knowledge in Alignment.
NAACL (Long Papers)
Runjin Chen, Gabriel J. Perin, Xuxi Chen, Xilun Chen, Yan Han, Nina S. T. Hirata, Junyuan Hong, Bhavya Kailkhura
2025 J jnl
Extracting and Understanding the Superficial Knowledge in Alignment.
CoRR
Runjin Chen, Gabriel J. Perin, Xuxi Chen, Xilun Chen, Yan Han, Nina S. T. Hirata, Junyuan Hong, Bhavya Kailkhura
2025 A* conf
From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications.
ICML
Ajay Kumar Jaiswal, Yifan Wang, Lu Yin, Shiwei Liu, Runjin Chen, Jiawei Zhao, Ananth Grama, Yuandong Tian, Zhangyang Wang
2025 A* conf
GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems.
WWW
Xinyi Wu, Donald Loveland, Runjin Chen, Yozen Liu, Xin Chen, Leonardo Neves, Ali Jadbabaie, Mingxuan Ju, Neil Shah, Tong Zhao
2025 J jnl
Inverse Scaling in Test-Time Compute.
CoRR
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
2025 J jnl
Inverse Scaling in Test-Time Compute.
Trans. Mach. Learn. Res.
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
2025 J jnl
LLMs Can Get "Brain Rot"!
CoRR
Shuo Xing, Junyuan Hong, Yifan Wang, Runjin Chen, Zhenyu Zhang, Ananth Grama, Zhengzhong Tu, Zhangyang Wang
2025 A* conf
Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning.
ICML
Ngoc Bui, Menglin Yang, Runjin Chen, Leonardo Neves, Mingxuan Ju, Rex Ying, Neil Shah, Tong Zhao
2025 J jnl
Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning.
CoRR
Ngoc Bui, Menglin Yang, Runjin Chen, Leonardo Neves, Mingxuan Ju, Rex Ying, Neil Shah, Tong Zhao
2025 J jnl
LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning.
CoRR
Gabriel J. Perin, Runjin Chen, Xuxi Chen, Nina S. T. Hirata, Zhangyang Wang, Junyuan Hong
2025 J jnl
More is Less: The Pitfalls of Multi-Model Synthetic Preference Data in DPO Safety Alignment.
CoRR
Yifan Wang, Runjin Chen, Bolian Li, David Cho, Yihe Deng, Ruqi Zhang, Tianlong Chen, Zhangyang Wang, Ananth Grama, Junyuan Hong
2025 J jnl
Persona Vectors: Monitoring and Controlling Character Traits in Language Models.
CoRR
Runjin Chen, Andy Arditi, Henry Sleight, Owain Evans, Jack Lindsey
2025 J jnl
SEAL: Steerable Reasoning Calibration of Large Language Models for Free.
CoRR
Runjin Chen, Zhenyu Zhang, Junyuan Hong, Souvik Kundu, Zhangyang Wang
2025 J jnl
VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction.
CoRR
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
2024 J jnl
Enhancing Item Tokenization for Generative Recommendation through Self-Improvement.
CoRR
Runjin Chen, Mingxuan Ju, Ngoc Bui, Dimosthenis Antypas, Stanley Cai, Xiaopeng Wu, Leonardo Neves, Zhangyang Wang, Neil Shah, Tong Zhao
2024 A* conf
Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding.
NeurIPS
Zhenyu Zhang, Runjin Chen, Shiwei Liu, Zhewei Yao, Olatunji Ruwase, Beidi Chen, Xiaoxia Wu, Zhangyang Wang
2024 J jnl
Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding.
CoRR
Zhenyu Zhang, Runjin Chen, Shiwei Liu, Zhewei Yao, Olatunji Ruwase, Beidi Chen, Xiaoxia Wu, Zhangyang Wang
2024 J jnl
GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems.
CoRR
Xinyi Wu, Donald Loveland, Runjin Chen, Yozen Liu, Xin Chen, Leonardo Neves, Ali Jadbabaie, Clark Mingxuan Ju, Neil Shah, Tong Zhao
2024 A* conf
LLaGA: Large Language and Graph Assistant.
ICML
Runjin Chen, Tong Zhao, Ajay Kumar Jaiswal, Neil Shah, Zhangyang Wang
2024 J jnl
LLaGA: Large Language and Graph Assistant.
CoRR
Runjin Chen, Tong Zhao, Ajay Jaiswal, Neil Shah, Zhangyang Wang
2024 — conf
Q-Hitter: A Better Token Oracle for Efficient LLM Inference via Sparse-Quantized KV Cache.
MLSys
Zhenyu Zhang, Shiwei Liu, Runjin Chen, Bhavya Kailkhura, Beidi Chen, Atlas Wang
2022 A conf
GCF-RD: A Graph-based Contrastive Framework for Semi-Supervised Learning on Relational Databases.
CIKM
Runjin Chen, Tong Li, Yanyan Shen, Luyu Qiu, Kaidi Li, Caleb Chen Cao
2021 A* conf
GNEM: A Generic One-to-Set Neural Entity Matching Framework.
WWW
Runjin Chen, Yanyan Shen, Dongxiang Zhang
2019 A* conf
Explaining Neural Networks Semantically and Quantitatively.
ICCV
Runjin Chen, Hao Chen, Ge Huang, Jie Ren, Quanshi Zhang
2019 A* conf
Towards a Deep and Unified Understanding of Deep Neural Models in NLP.
ICML
Chaoyu Guan, Xiting Wang, Quanshi Zhang, Runjin Chen, Di He, Xing Xie
2018 J jnl
Explaining Neural Networks Semantically and Quantitatively.
CoRR
Runjin Chen, Hao Chen, Ge Huang, Jie Ren, Quanshi Zhang