2 citations · 2 across the 3 of their papers we have counts for
9 papers
Lossless Tensor Compression as Program Synthesis
Jieke Shi, Junda He, Wenjia Jiang +11
Model checkpoints are growing in both number and size, which makes archival, transfer, and deployment increasingly costly. General-purpose compressors can reduce storage requiremen…
Forecasting Side Effects of Activation Steering
Chong Yong Ong, Alson Wei Jie Sim, Peixin Zhang +1
Activation steering modifies a language model by adding a learned direction to its hidden activations, enabling targeted behavioral changes without retraining. While effective, ste…
Efficient and Universal Watermarking for LLM-Generated Code Detection
Boquan Li, Zirui Fu, Mengdi Zhang +3
Large language models (LLMs) have significantly enhanced the usability of AI-generated code, providing effective assistance to programmers. This advancement also raises ethical and…
DDOR: Delta Debugging for Explainable Overrefusal Testing and Repair
Qinyan Zhou, Peixin Zhang, Jun Sun +2
While safety alignment and guardrails help large language models (LLMs) avoid harmful outputs, they can also induce overrefusal, i.e., unwarranted rejection of benign queries that…
ClawGuard: A Runtime Security Framework for Tool-Augmented LLM Agents Against Indirect Prompt Injection
Wei Zhao, Zhe Li, Peixin Zhang +1
Tool-augmented Large Language Model (LLM) agents have demonstrated impressive capabilities in automating complex, multi-step real-world tasks, yet remain vulnerable to indirect pro…
Towards Provably Unlearnable Examples via Bayes Error Optimisation
Ruihan Zhang, Jun Sun, Ee-Peng Lim +1
The recent success of machine learning models, especially large-scale classifiers and language models, relies heavily on training with massive data. These data are often collected…