12 citations · 37 across the 12 of their papers we have counts for
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cs.AI2025
LM Agents May Fail to Act on Their Own Risk Knowledge
Yuzhi Tang, Tianxiao Li, Elizabeth Li +3
Language model (LM) agents have demonstrated significant potential for automating real-world tasks, yet they pose a diverse array of potential, severe risks in safety-critical scen…
cs.AI2024
APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts
Honghua Dong, Qidong Su, Yubo Gao +5
Large Language Models (LLMs) have become increasingly capable of handling diverse tasks with the aid of well-crafted prompts and integration of external tools, but as task complexi…
cs.AI2023★ 6 cited
Identifying the Risks of LM Agents with an LM-Emulated Sandbox
Yangjun Ruan, Honghua Dong, Andrew Wang +6
Recent advances in Language Model (LM) agents and tool use, exemplified by applications like ChatGPT Plugins, enable a rich set of capabilities but also amplify potential risks - s…