Ajay Kumar Jaiswal
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
15
Venues
3
Active years
2022–2025
Best venue rank
A*
Where they publish
Papers
15 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | EMNLP | Bit-Flip Error Resilience in LLMs: A Comprehensive Analysis and Defense Framework. | Yuhang Chen, Zhen Tan, Ajay Kumar Jaiswal, Huaizhi Qu, Xinyu Zhao, Qi Lin, Yu Cheng, Andrew Kwong, Zhichao Cao, Tianlong Chen |
| 2025 | ICLR | SEBRA : Debiasing through Self-Guided Bias Ranking. | Adarsh Kappiyath, Abhra Chaudhuri, Ajay Kumar Jaiswal, Ziquan Liu, Yunpeng Li, Xiatian Zhu, Lu Yin |
| 2025 | ICML | From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications. | Ajay Kumar Jaiswal, Yifan Wang, Lu Yin, Shiwei Liu, Runjin Chen, Jiawei Zhao, Ananth Grama, Yuandong Tian, Zhangyang Wang |
| 2024 | ICLR | Compressing LLMs: The Truth is Rarely Pure and Never Simple. | Ajay Kumar Jaiswal, Zhe Gan, Xianzhi Du, Bowen Zhang, Zhangyang Wang, Yinfei Yang |
| 2024 | ICML | Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs. | Lu Yin, Ajay Kumar Jaiswal, Shiwei Liu, Souvik Kundu, Zhangyang Wang |
| 2024 | ICML | Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. | 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 | ICML | LLaGA: Large Language and Graph Assistant. | Runjin Chen, Tong Zhao, Ajay Kumar Jaiswal, Neil Shah, Zhangyang Wang |
| 2024 | ICML | Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression. | 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 | ICML | Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once. | Zhangheng Li, Shiwei Liu, Tianlong Chen, Ajay Kumar Jaiswal, Zhenyu Zhang, Dilin Wang, Raghuraman Krishnamoorthi, Shiyu Chang, Zhangyang Wang |
| 2023 | ICLR | Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. | Tianlong Chen, Zhenyu Zhang, Ajay Kumar Jaiswal, Shiwei Liu, Zhangyang Wang |
| 2023 | ICLR | Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! | Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang |
| 2023 | ICML | Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. | Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang |
| 2023 | ICML | Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. | Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang |
| 2023 | ICML | Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation. | Wenqing Zheng, S. P. Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, Zhangyang Wang |
| 2022 | ICML | Training Your Sparse Neural Network Better with Any Mask. | Ajay Kumar Jaiswal, Haoyu Ma, Tianlong Chen, Ying Ding, Zhangyang Wang |