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cs.LG2025
How do Transformers Learn Implicit Reasoning?
Jiaran Ye, Zijun Yao, Zhidian Huang +8
Recent work suggests that large language models (LLMs) can perform multi-hop reasoning implicitly -- producing correct answers without explicitly verbalizing intermediate steps --…
cs.LG2024
Tracing Privacy Leakage of Language Models to Training Data via Adjusted Influence Functions
Jinxin Liu, Zao Yang
The responses generated by Large Language Models (LLMs) can include sensitive information from individuals and organizations, leading to potential privacy leakage. This work implem…
cs.LG2024★ 2 cited
Scalable and Effective Arithmetic Tree Generation for Adder and Multiplier Designs
Yao Lai, Jinxin Liu, David Z. Pan +1
Across a wide range of hardware scenarios, the computational efficiency and physical size of the arithmetic units significantly influence the speed and footprint of the overall har…