most citedPerception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

CulturalMenuBench: Probing the Knowledge-Application Gap in Multimodal Culinary Reasoning

Bo Zeng, Linfeng Gao, Peiqin Lin +9

Multimodal language models achieve near-ceiling scores on food recognition benchmarks, yet it remains unclear whether this success reflects genuine cultural understanding or mere v…

cs.CL2026

VIDA: A Dataset for Visually Dependent Ambiguity in Multimodal Machine Translation

Jingheng Pan, Xintong Wang, Longyue Wang +3

Ambiguity resolution is a key challenge in multimodal machine translation (MMT), where models must genuinely leverage visual input to map an ambiguous expression to its intended me…

cs.CV2025

Rethinking Multilingual Vision-Language Translation: Dataset, Evaluation, and Adaptation

Xintong Wang, Jingheng Pan, Yixiao Liu +8

Vision-Language Translation (VLT) is a challenging task that requires accurately recognizing multilingual text embedded in images and translating it into the target language with t…

cs.CV2025★ 1 cited

Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models

Yunxin Li, Zhenyu Liu, Zitao Li +19

Reasoning lies at the heart of intelligence, shaping the ability to make decisions, draw conclusions, and generalize across domains. In artificial intelligence, as systems increasi…

cs.CL2025★ 1 cited

The Bitter Lesson Learned from 2,000+ Multilingual Benchmarks

Minghao Wu, Weixuan Wang, Sinuo Liu +7

As large language models (LLMs) continue to advance in linguistic capabilities, robust multilingual evaluation has become essential for promoting equitable technological progress.…