Ajay Kumar Jaiswal

22 papers A* 15Journal 5Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Bit-Flip Error Resilience in LLMs: A Comprehensive Analysis and Defense Framework. EMNLP Yuhang Chen, Zhen Tan, Ajay Kumar Jaiswal, Huaizhi Qu, Xinyu Zhao, Qi Lin, Yu Cheng, Andrew Kwong, Zhichao Cao, Tianlong Chen
2025	J	`jnl`	Double-Checker: Enhancing Reasoning of Slow-Thinking LLMs via Self-Critical Fine-Tuning. CoRR Xin Xu, Tianlong Chen, Fan Zhang, Wanlong Liu, Pengxiang Li, Ajay Kumar Jaiswal, Yuchen Yan, Jishan Hu, Yang Wang, Hao Chen, Shiwei Liu, Shizhe Diao, Can Yang, Lu Yin
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	J	`jnl`	GPAS: Accelerating Convergence of LLM Pretraining via Gradient-Preserving Activation Scaling. CoRR Tianlong Chen, Xin Xu, Zijing Liu, Pengxiang Li, Xinyuan Song, Ajay Kumar Jaiswal, Fan Zhang, Jishan Hu, Yang Wang, Hao Chen, Shizhe Diao, Shiwei Liu, Yu Li, Yin Lu, Can Yang
2025	—	`conf`	Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients. CPAL Zhenyu Zhang, Ajay Kumar Jaiswal, Lu Yin, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang
2025	A*	`conf`	SEBRA : Debiasing through Self-Guided Bias Ranking. ICLR Adarsh Kappiyath, Abhra Chaudhuri, Ajay Kumar Jaiswal, Ziquan Liu, Yunpeng Li, Xiatian Zhu, Lu Yin
2024	A*	`conf`	Compressing LLMs: The Truth is Rarely Pure and Never Simple. ICLR Ajay Kumar Jaiswal, Zhe Gan, Xianzhi Du, Bowen Zhang, Zhangyang Wang, Yinfei Yang
2024	A*	`conf`	Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression. ICML Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie, Kelsey Lieberman, James Diffenderfer, Brian R. Bartoldson, Ajay Kumar Jaiswal, Kaidi Xu, Bhavya Kailkhura, Dan Hendrycks, Dawn Song, Zhangyang Wang, Bo Li
2024	J	`jnl`	Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning. CoRR Abhinav Bandari, Lu Yin, Cheng-Yu Hsieh, Ajay Kumar Jaiswal, Tianlong Chen, Li Shen, Ranjay Krishna, Shiwei Liu
2024	A*	`conf`	Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs. ICML Lu Yin, Ajay Kumar Jaiswal, Shiwei Liu, Souvik Kundu, Zhangyang Wang
2024	A*	`conf`	LLaGA: Large Language and Graph Assistant. ICML Runjin Chen, Tong Zhao, Ajay Kumar Jaiswal, Neil Shah, Zhangyang Wang
2024	A*	`conf`	Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. ICML Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Gen Li, Ajay Kumar Jaiswal, Mykola Pechenizkiy, Yi Liang, Michael Bendersky, Zhangyang Wang, Shiwei Liu
2024	—	`conf`	Path-RAG: Knowledge-Guided Key Region Retrieval for Open-ended Pathology Visual Question Answering. ML4H@NeurIPS Awais Naeem, Tianhao Li, Huang-Ru Liao, Jiawei Xu, Aby M. Mathew, Zehao Zhu, Zhen Tan, Ajay Kumar Jaiswal, Raffi A. Salibian, Ziniu Hu, Tianlong Chen, Ying Ding
2024	J	`jnl`	Path-RAG: Knowledge-Guided Key Region Retrieval for Open-ended Pathology Visual Question Answering. CoRR Awais Naeem, Tianhao Li, Huang-Ru Liao, Jiawei Xu, Aby M. Mathew, Zehao Zhu, Zhen Tan, Ajay Kumar Jaiswal, Raffi A. Salibian, Ziniu Hu, Tianlong Chen, Ying Ding
2024	A*	`conf`	Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once. ICML Zhangheng Li, Shiwei Liu, Tianlong Chen, Ajay Kumar Jaiswal, Zhenyu Zhang, Dilin Wang, Raghuraman Krishnamoorthi, Shiyu Chang, Zhangyang Wang
2023	A*	`conf`	Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. ICML Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang
2023	A*	`conf`	Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. ICML Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang
2023	A*	`conf`	Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation. ICML Wenqing Zheng, S. P. Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, Zhangyang Wang
2023	J	`jnl`	Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation. CoRR Wenqing Zheng, S. P. Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, Zhangyang Wang
2023	A*	`conf`	Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. ICLR Tianlong Chen, Zhenyu Zhang, Ajay Kumar Jaiswal, Shiwei Liu, Zhangyang Wang
2023	A*	`conf`	Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! ICLR Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang
2022	A*	`conf`	Training Your Sparse Neural Network Better with Any Mask. ICML Ajay Kumar Jaiswal, Haoyu Ma, Tianlong Chen, Ying Ding, Zhangyang Wang