collaborators

6 papers

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.CL2026

Overview of FinMMEval 2026 Task 2: Multilingual Financial Short-Answer Question Answering

Zhuohan Xie, Xueqing Peng, Georgi Georgiev +18

FinMMEval 2026 Task 2 evaluates short-answer financial question answering over multilingual evidence. Each final-test item pairs an English question with financial statements and n…

cs.CL2026

Overview of FinMMEval 2026 Task 1: Multilingual Financial Multiple-Choice Question Answering

Zhuohan Xie, Yuyang Dai, Rania Elbadry +18

FinMMEval 2026 Task 1 evaluates multilingual financial multiple-choice question answering in English, Chinese, Arabic, and Hindi. The task tests whether systems can select the corr…

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…

q-fin.ST2026

RealFin: How Well Do LLMs Reason About Finance When Users Leave Things Unsaid?

Yuyang Dai, Yan Lin, Zhuohan Xie +1

Reliable financial reasoning requires knowing not only how to answer, but also when an answer cannot be justified. In real financial practice, problems often rely on implicit assum…

cs.CL2026

The CLEF-2026 FinMMEval Lab: Multilingual and Multimodal Evaluation of Financial AI Systems

Zhuohan Xie, Rania Elbadry, Fan Zhang +12

We present the setup and the tasks of the FinMMEval Lab at CLEF 2026, which introduces the first multilingual and multimodal evaluation framework for financial Large Language Model…