ASPS-L2.1
Alternating Balancing Sums for Accurate Low-Power Dot Products
Vikas Natesh, H.T. Kung, Harvard University, United States of America
Session:
ASPS-L2: resource-efficient and generative AI systems Oral
Track:
Applied Signal Processing Systems [AS]
Location:
Room 116
Presentation Time:
Wed, 6 May, 14:00 - 14:20
Presentation
Discussion
Resources
No resources available.
Session ASPS-L2
ASPS-L2.1: Alternating Balancing Sums for Accurate Low-Power Dot Products
Vikas Natesh, H.T. Kung, Harvard University, United States of America
ASPS-L2.2: ADAPTING WHISPER FOR PADDING-FREE INFERENCE USING AN ENCODER ATTENTION MASK AND KNOWLEDGE DISTILLATION
Amin Abdaoui, Abdelmoumene Boumadane, Trideba PADHI, Nancy BERTIN, Nathan SOUVIRAA LABASTIE, Serge LE HUITOUZE, Kyu Jeong Han, Oracle AI, France
ASPS-L2.3: EXPERIENCE-DRIVEN DYNAMIC EXITS FOR LLMS WITH REINFORCEMENT LEARNING
Yanyu Zhu, Hoilam Pao, Hai-Tao Zheng, Tsinghua Shenzhen International Graduate School, China; Niu Hu, Wei Guo, Huawei, China; Shaoxiong Zhan, Tsinghua Shenzhen International Graduate School, China; Boyu Lai, Northwestern Polytechnical University, China; Zitai Wang, Yongqin Zeng, Tsinghua Shenzhen International Graduate School, China
ASPS-L2.4: SEMANTICACHE: EFFICIENT KV CACHE COMPRESSION VIA SEMANTIC CHUNKING AND CLUSTERED MERGING
Shunlong Wu, Hai Lin, Shaoshen Chen, Tingwei Lu, Yongqin Zeng, Shaoxiong Zhan, Hai-Tao Zheng, Tsinghua University, China; Hong-Gee Kim, Seoul National University, Korea, Republic of
ASPS-L2.5: ITERATIVE REDUNDANCY-BASED HEAD PRUNING FOR EFFICIENT SELF-SUPERVISED SPEECH RECOGNITION MODELS
Sang-Heon Jeong, Dong-Hyun Kim, Joon-Hyuk Chang, Hanyang University, Korea, Republic of
ASPS-L2.6: COMNET: A COMPLEMENTARY PROTOTYPES-GUIDED RECONSTRUCTION FRAMEWORK FOR MULTI-CLASS ANOMALY DETECTION
Xiaodong Wang, Xiaolong Huang, Fei Yan, Hua Guo, Zhiqiang Zeng, Junwen Lu, Xiamen University of Technology, China
Contacts