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Fangqi Lou

2 accepted papers

2026

HiFICL: High-Fidelity In-Context Learning for Multimodal Tasks

CVPR 2026

In-Context Learning (ICL) is a significant paradigm for Large Multimodal Models (LMMs), using a few in-context demonstrations (ICDs) for new task adaptation. However, its performance is sensitive to demonstration configurations and computationally expensive. Mathematically, the influence of these de

Cited by 0SourcecodeScholar
2025

VisFinEval: A Scenario-Driven Chinese Multimodal Benchmark for Holistic Financial Understanding

EMNLP 2025

Multimodal large language models (MLLMs) hold great promise for automating complex financial analysis. To comprehensively evaluate their capabilities, we introduce VisFinEval, the first large-scale Chinese benchmark that spans the full front-middle-back office lifecycle of financial tasks. VisFinEva