217 citations · 1.8k across the 154 of their papers we have counts for
165 papers
Reading Position Is the Baseline to Beat: A Time-Ordered Evaluation of Personalised Highlight Prediction
Kazuki Nakayashiki, Keisuke Watanabe
A reader's first highlights on a page are the cheapest personal signal a reading product has. The natural plan is to suggest what similar earlier readers marked, and to judge the r…
Secure Speculative Decoding for Large Language Models
Yichi Zhang, Zhiqi Wang, Neil Gong +1
Speculative decoding accelerates inference for a large language model (LLM), referred to as the \emph{target model}, by first using a smaller model, referred to as the \emph{draft…
Self-Evolving Coding Rules for AI Coding Agents
Zhengyuan Jiang, Reachal Wang, Yuepeng Hu +3
The performance of AI coding agents is highly dependent on their underlying coding rules. However, existing coding rules are typically hand-crafted and fixed, making the process la…
Divide and Doubt: Diverse Distributed Poisoning for Retrieval-Augmented Generation
Tianhao Chen, Yuhan Wei, Weifei Jin +3
Multi-passage corpus poisoning often repeats one target claim across similar documents, creating correlated lexical and semantic patterns that similarity- and conflict-aware defens…
LongPIBench: A Long-Context Benchmark for Prompt Injection
Yupei Liu, Yuqi Jia, Neil Zhenqiang Gong +1
Prompt injection attacks pose a serious security risk to large language models in real-world applications. However, existing prompt injection benchmarks primarily focus on short-co…
ContextLeak: Exfiltrating LLM Agent Context via Malicious Tools
Yuqi Jia, Ruiqi Wang, Patrick Li +3
Exfiltrating an LLM agent's runtime context -- such as the user prompt, execution trajectory, and tool list -- poses severe security and privacy risks to users. Such attacks can be…