From the 1 of 12 linked papers with an AI index.
12 papers
Computational Humor with Multimodal LLMs: Methods, Datasets, Evaluation, and Challenges
Tuo Liang, Zhe Hu, Disheng Liu +2
Multimodal humor in memes, cartoons, and comics remains difficult for AI systems because intended meaning depends on non-literal mechanisms, shared cultural knowledge, and communic…
ProAct: A Benchmark and Multimodal Framework for Structure-Aware Proactive Response
Xiaomeng Zhu, Fengming Zhu, Weijie Zhou +8
The paper introduces ProAct-75, a benchmark of 75 proactive tasks with step‑level annotations and task graphs, and presents ProAct-Helper, a multimodal LLM that uses these graphs f…
VIABLE: A Visually Impaired Assistance Benchmark for VLM-as-a-Judge Evaluation
Yi Zhao, Siqi Wang, Zhe Hu +2
AI-based Visually Impaired Assistance (VIA) remains challenging, largely due to the high cost of human evaluation. The VLM-as-a-Judge paradigm may offer a promising alternative, al…
When 'YES' Meets 'BUT': Can Large Models Comprehend Contradictory Humor Through Comparative Reasoning?
Tuo Liang, Zhe Hu, Jing Li +8
Understanding humor-particularly when it involves complex, contradictory narratives that require comparative reasoning-remains a significant challenge for large vision-language mod…
Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions
Zhe Hu, Tuo Liang, Jing Li +5
Recent advancements in large multimodal language models have demonstrated remarkable proficiency across a wide range of tasks. Yet, these models still struggle with understanding t…
Praxis-VLM: Vision-Grounded Decision Making via Text-Driven Reinforcement Learning
Zhe Hu, Jing Li, Zhongzhu Pu +2
Vision Language Models exhibit impressive performance for various tasks, yet they often lack the sophisticated situational reasoning required for complex decision-making. This pape…