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cs.AI2026

Jumping the Line: Exploiting Length Predictions in LLM Scheduling

Yuyang Dai, Rana Shahout, Mahmood Sharif

Efficient request scheduling is increasingly important for reducing completion time in large language model (LLM) serving. Size-based policies such as Shortest Job First prioritize…

cs.AI2026

Seeing Is Not Deciding: Can Multimodal LLMs Act as Effective CEOs?

Yuyang Dai, Xueqing Peng, Yuxia Wang +2

Large language models are increasingly applied as autonomous decision-making agents. However, in executive business decisions, existing benchmarks are limited to textonly settings.…

cs.AI2026

AI YOU Town: Make Friends and Money with Your Digital Twin

Yan Lin, Yuyang Dai, Jiahui Geng +1

Existing approaches to infer user traits and generate responses consistent with a persona rely on static prompting. They lack calibrated uncertainty, ignore sequential evidence, an…

cs.AI2026

Can LLMs Be CEOs? Benchmarking Strategic Resource Reallocation with Multi-Role Agent Simulation

Yuyang Dai, Xueqing Peng, Lingfei Qian +1

Evaluating the decision-making capabilities of large language models (LLMs) is a growing research priority, yet existing benchmarks focus on isolated cognitive tasks such as reason…

cs.AI2026

Herculean: An Agentic Benchmark for Financial Intelligence

Xueqing Peng, Zhuohan Xie, Yupeng Cao +60

As AI agents advance, the central question is no longer whether they can solve isolated financial tasks, but whether their capabilities generalize across complete professional work…

cs.AI2026

EpiGraph: Building Generalists for Evidence-Intensive Epilepsy Reasoning in the Wild

Yuyang Dai, Zheng Chen, Jathurshan Pradeepkumar +4

Epilepsy diagnosis and treatment require evidence-intensive reasoning across heterogeneous clinical knowledge, including biosignal patterns, genetic mechanisms, pharmacogenomics, t…

cs.AI2026

Beyond 0-100: How Confidence Scale Design Shapes Verbalized Confidence and LLM Metacognition

Yuyang Dai, Yuxia Wang

Verbalized confidence, in which LLMs report a numerical certainty score, is widely used to estimate uncertainty in black-box settings, yet the confidence scale itself (typically 0-…