1 citations · 1 across the 3 of their papers we have counts for
5 papers
Every Token Leaves a Ripple in the Stream of Thought: Eliciting Model-Internal Token Saliency for Chain-of-Thought Compression
Tianyi Zhao, Yinhan He, Wendy Zheng +1
Chain-of-thought (CoT) reasoning improves multi-step problem solving, but long reasoning traces inflate inference cost. Token-level CoT compression reduces this cost by pruning ful…
Addressing the Reasoning Gap: Mechanistic Circuit-Based Knowledge Editing in Large Language Models
Tianyi Zhao, Yinhan He, Wendy Zheng +1
Deploying Large Language Models (LLMs) in real-world dynamic environments raises the challenge of updating their pre-trained knowledge. While existing knowledge editing methods can…
Robust and Scalable Model Editing for Large Language Models
Yingfa Chen, Zhengyan Zhang, Xu Han +6
Large language models (LLMs) can make predictions using parametric knowledge--knowledge encoded in the model weights--or contextual knowledge--knowledge presented in the context. I…
ProSparse: Introducing and Enhancing Intrinsic Activation Sparsity within Large Language Models
Chenyang Song, Xu Han, Zhengyan Zhang +8
Activation sparsity refers to the existence of considerable weakly-contributed elements among activation outputs. As a prevalent property of the models using the ReLU activation fu…
ConPET: Continual Parameter-Efficient Tuning for Large Language Models
Chenyang Song, Xu Han, Zheni Zeng +5
Continual learning necessitates the continual adaptation of models to newly emerging tasks while minimizing the catastrophic forgetting of old ones. This is extremely challenging f…