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cs.CV2025
FinMMR: Make Financial Numerical Reasoning More Multimodal, Comprehensive, and Challenging
Zichen Tang, Haihong E, Jiacheng Liu +18
We present FinMMR, a novel bilingual multimodal benchmark tailored to evaluate the reasoning capabilities of multimodal large language models (MLLMs) in financial numerical reasoni…
cs.CL2025★ 5 cited
FinanceReasoning: Benchmarking Financial Numerical Reasoning More Credible, Comprehensive and Challenging
Zichen Tang, Haihong E, Ziyan Ma +10
We introduce FinanceReasoning, a novel benchmark designed to evaluate the reasoning capabilities of large reasoning models (LRMs) in financial numerical reasoning problems. Compare…
cs.LG2025
Understanding In-context Learning of Addition via Activation Subspaces
Xinyan Hu, Kayo Yin, Michael I. Jordan +2
To perform few-shot learning, language models extract signals from a few input-label pairs, aggregate them into a learned prediction rule, and apply this rule to new inputs. How is…