Explaining Neural Networks Semantically and Quantitatively. - Runjin Chen; Hao Chen 099; Ge Huang; Jie Ren 018; Quanshi Zhang (ICCV, 2019)

Towards a Deep and Unified Understanding of Deep Neural Models in NLP. - Chaoyu Guan; Xiting Wang; Quanshi Zhang; Runjin Chen; Di He 001; Xing Xie 001 (ICML, 2019)

GNEM: A Generic One-to-Set Neural Entity Matching Framework. - Runjin Chen; Yanyan Shen; Dongxiang Zhang (WWW, 2021)

GCF-RD: A Graph-based Contrastive Framework for Semi-Supervised Learning on Relational Databases. - Runjin Chen; Tong Li 017; Yanyan Shen; Luyu Qiu; Kaidi Li; Caleb Chen Cao (CIKM, 2022)

LLaGA: Large Language and Graph Assistant. - Runjin Chen; Tong Zhao 003; Ajay Kumar Jaiswal; Neil Shah; Zhangyang Wang (ICML, 2024)

Q-Hitter: A Better Token Oracle for Efficient LLM Inference via Sparse-Quantized KV Cache. - Zhenyu Zhang 015; Shiwei Liu 003; Runjin Chen; Bhavya Kailkhura; Beidi Chen; Atlas Wang (MLSys, 2024)

Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding. - Zhenyu Zhang 015; Runjin Chen; Shiwei Liu 003; Zhewei Yao; Olatunji Ruwase; Beidi Chen; Xiaoxia Wu; Zhangyang Wang (NeurIPS, 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 003 (CoRR, 2024)

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems. - Xinyi Wu 003; Donald Loveland; Runjin Chen; Yozen Liu; Xin Chen 085; Leonardo Neves; Ali Jadbabaie; Clark Mingxuan Ju; Neil Shah; Tong Zhao 003 (CoRR, 2024)

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 (NAACL (Long Papers), 2025)

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems. - Xinyi Wu 003; Donald Loveland; Runjin Chen; Yozen Liu; Xin Chen 085; Leonardo Neves; Ali Jadbabaie; Mingxuan Ju; Neil Shah; Tong Zhao 003 (WWW, 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 001; Zhangyang Wang; Ananth Grama; Junyuan Hong (CoRR, 2025)

SEAL: Steerable Reasoning Calibration of Large Language Models for Free. - Runjin Chen; Zhenyu Zhang 015; Junyuan Hong; Souvik Kundu 009; Zhangyang Wang (CoRR, 2025)

VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction. - Zhiwen Fan; Jian Zhang; Renjie Li 003; Junge Zhang; Runjin Chen; Hezhen Hu; Kevin Wang; Huaizhi Qu; Dilin Wang; Zhicheng Yan 001; Hongyu Xu; Justin Theiss; et al. (CoRR, 2025)

Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning. - Ngoc Bui; Menglin Yang 001; Runjin Chen; Leonardo Neves; Mingxuan Ju; Rex Ying; Neil Shah; Tong Zhao 003 (CoRR, 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, 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; et al. (CoRR, 2025)

Persona Vectors: Monitoring and Controlling Character Traits in Language Models. - Runjin Chen; Andy Arditi; Henry Sleight; Owain Evans; Jack Lindsey (CoRR, 2025)