5 papers · 1 filter
Grounded Chess Reasoning in Language Models via Master Distillation
Zhenwei Tang, Qianfeng Wen, Seth Grief-Albert +4
Language models often lack grounded reasoning capabilities in specialized domains where training data is scarce but bespoke systems excel. We introduce a general framework for dist…
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…
-Bench: Evaluating Conversational Agents in a Dual-Control Environment
Victor Barres, Honghua Dong, Soham Ray +2
Existing benchmarks for conversational AI agents simulate single-control environments, where only the AI agent can use tools to interact with the world, while the user remains a pa…
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…
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…