Tool-using LLM agents repeatedly face decision points under uncertainty, choosing between autonomous action, additional information gathering, and human escalation. These decisions require balancing task success against interaction cost and the risk of irreversible errors. Learning to make these trade-offs is challengi...
Qi-Sai Liu, Qing-Yue Jiao, Bang-Wei Guo et al.· 0 citations
Existing steering benchmarks are built around simplified, isolated generation tasks and evaluate a single behavioral attribute under controlled settings that do not reflect the diversity and complexity of practical deployment. As a result, performance on these benchmarks provides only a limited picture of how steering...
Xin-Yi Cai, Bin Hu, Ming-Yu Jin et al.· 0 citations
Multimodal models and agents have emerged to enable AI systems to learn from and interact with the real world more like humans by integrating information across multiple modalities. However, enabling multimodal agents to continually acquire useful information from complex, heterogeneous multimodal data remains a signif...
Ming-Hao Guo, Qing-Yue Jiao, Xiu-Jin Liu et al.· 0 citations
Sampling multiple solutions spends computation on intermediate deductions and unfinished arguments as well as final answers. We introduce ReSolve, a training-free inference procedure that reuses this candidate reasoning through selective generative moderation. An answer-distribution controller invokes a model to examin...
Bang Yang, Jia-Jun Fan, Hong-Bo Ma et al.· 0 citations
This work presents OpenPM, an auditable point-in-time evaluation framework for LLM portfolio-management agents, and builds a reference agent named the tiered allocator, where typed analysts score candidates, a constructor LLM proposes weights, and a deterministic critic guarantees feasibility.
Xinying Cai, Ming-Hao Guo, Jiahe Liu et al.· 1 citation
Pera describes a persistent agent organized around perception and control components that continually perceive service-relevant signals from episodic task executions, internal context, and changes in the surrounding environment, and use these signals to construct lifecycle tasks.
Shi-Han Dou, Haoxiang Jia, Shichun Liu et al.· 1 citation
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