5 papers
Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning
Weitao Feng, Lixu Wang, Peizhuo Lv +5
As large language models (LLMs) continue to grow in capability, so do the risks of harmful misuse through fine-tuning. While most prior studies assume that attackers rely on superv…
Shop-R1: Rewarding LLMs to Simulate Human Behavior in Online Shopping via Reinforcement Learning
Yimeng Zhang, Tian Wang, Jiri Gesi +14
Large Language Models (LLMs) have recently demonstrated strong potential in generating 'believable human-like' behavior in web environments. Prior work has explored augmenting trai…
STEP-LLM: Generating CAD STEP Models from Natural Language with Large Language Models
Xiangyu Shi, Junyang Ding, Xu Zhao +8
Computer-aided design (CAD) is vital to modern manufacturing, yet model creation remains labor-intensive and expertise-heavy. To enable non-experts to translate intuitive design in…
Shedding Light on VLN Robustness: A Black-box Framework for Indoor Lighting-based Adversarial Attack
Chenyang Li, Wenbing Tang, Yihao Huang +4
Vision-and-Language Navigation (VLN) agents have made remarkable progress, but their robustness remains insufficiently studied. Existing adversarial evaluations often rely on pertu…
See, Think, Act: Online Shopper Behavior Simulation with VLM Agents
Yimeng Zhang, Jiri Gesi, Ran Xue +10
LLMs have recently demonstrated strong potential in simulating online shopper behavior. Prior work has improved action prediction by applying SFT on action traces with LLM-generate…