54 citations · 70 across the 12 of their papers we have counts for
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cs.CL2026
Beyond Tokens: A Survey on Decoding Methods for Large Language and Vision-Language Models
Haoran Wang, Xiongxiao Xu, Philip S. Yu +1
Large language models (LLMs) and large vision-language models (LVLMs) have demonstrated impressive generative capabilities, yet ensuring their outputs align with user intent is sti…
cs.SE2026
Dependency-Guided Code Generation: Structured Matrix Decomposition and Consistency-Guided Refinement
Mingqiao Mo, Yangchen Zeng, Zikai Xiao +7
The increasing complexity of modern software systems has made automated code generation a fundamental task in software engineering. However, existing approaches often fail to adequ…
cs.CL2026
Do LLMs Know What Is Private Internally? Probing and Steering Contextual Privacy Norms in Large Language Model Representations
Haoran Wang, Li Xiong, Kai Shu
Large language models (LLMs) are increasingly deployed in high-stakes settings, yet they frequently violate contextual privacy by disclosing private information in situations where…