1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.SE2026★ 1 cited
Neuron-Guided Interpretation of Code LLMs: Where, Why, and How?
Zhe Yin, Xiaodong Gu, Beijun Shen
Code language models excel on code intelligence tasks, yet their internal interpretability is underexplored. Existing neuron interpretability techniques from NLP are suboptimal for…
cs.CL2025
Anti-adversarial Learning: Desensitizing Prompts for Large Language Models
Xuan Li, Zhe Yin, Xiaodong Gu +1
With the widespread use of LLMs, preserving privacy in user prompts has become crucial, as prompts risk exposing privacy and sensitive data to the cloud LLMs. Traditional technique…
cs.LG2025
Virtual Width Networks
Seed, Baisheng Li, Banggu Wu +115
We introduce Virtual Width Networks (VWN), a framework that delivers the benefits of wider representations without incurring the quadratic cost of increasing the hidden size. VWN d…