5 citations · 8 across the 10 of their papers we have counts for
10 papers
APSQ: Additive Partial Sum Quantization with Algorithm-Hardware Co-Design
Yonghao Tan, Pingcheng Dong, Yongkun Wu +8
DNN accelerators, significantly advanced by model compression and specialized dataflow techniques, have marked considerable progress. However, the frequent access of high-precision…
End-to-End Dialog Neural Coreference Resolution: Balancing Efficiency and Accuracy in Large-Scale Systems
Zhang Dong, Songhang deng, Mingbang Wang +4
Large-scale coreference resolution presents a significant challenge in natural language processing, necessitating a balance between efficiency and accuracy. In response to this cha…
UnifiedMLLM: Enabling Unified Representation for Multi-modal Multi-tasks With Large Language Model
Zhaowei Li, Wei Wang, YiQing Cai +7
Significant advancements has recently been achieved in the field of multi-modal large language models (MLLMs), demonstrating their remarkable capabilities in understanding and reas…
On the Temperature of Machine Learning Systems
Dong Zhang
We develop a thermodynamic theory for machine learning (ML) systems. Similar to physical thermodynamic systems which are characterized by energy and entropy, ML systems possess the…
SpeechAlign: Aligning Speech Generation to Human Preferences
Dong Zhang, Zhaowei Li, Shimin Li +4
Speech language models have significantly advanced in generating realistic speech, with neural codec language models standing out. However, the integration of human feedback to ali…
Genetic Quantization-Aware Approximation for Non-Linear Operations in Transformers
Pingcheng Dong, Yonghao Tan, Dong Zhang +11
Non-linear functions are prevalent in Transformers and their lightweight variants, incurring substantial and frequently underestimated hardware costs. Previous state-of-the-art wor…