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Reza Shirkavand · Xiaokai Wei · Chen Wang · Zheng Hui · Heng Huang · Michelle Gong
Yijiang River Dong · Tiancheng Hu · Zheng Hui · Caiqi Zhang · Ivan Vulić · Andreea Bobu · Nigel Collier
Large Language Model (LLM) agents deployed for real-world tasks face a fundamental dilemma: user requests are underspecified, yet agents must decide whether to act on incomplete information or interrupt users for clarification. Existing approaches either rely on brittle confidence thresholds that...
Zheng Hui · Yijiang River Dong · Sanhanat Sivapiromrat · Ehsan Shareghi · Nigel Collier
When users submit queries to Large Language Models (LLMs), their prompts can often contain sensitive data, forcing a difficult choice: Send the query to a powerful proprietary LLM providers to achieving state-of-the-art performance and risk data exposure, or relying on smaller, local models guara...