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20212026
most citedLanguage Models with Image Descriptors are Strong Few-Shot Video-Language Learners

52 citations · 98 across the 19 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

Brick-Composer: Using MLLMs for Assembly with Diverse Bricks

Jiateng Liu, Bingxuan Li, Zhenhailong Wang +8

We dream of AI agents that can read arbitrary designs and construct real-world objects from reusable building blocks. As a first step toward this vision, we study whether multimoda…

cs.AI2026

Advancing Creative Physical Intelligence in Large Multimodal Models

Cheng Qian, Hyeonjeong Ha, Jiayu Liu +10

Large multimodal models (LMMs) have rapidly advanced in perception and reasoning; however, it remains unclear whether these capabilities generalize to discovering visually grounded…

cs.AI2026

CreativityBench: Evaluating Agent Creative Reasoning via Affordance-Based Tool Repurposing

Cheng Qian, Hyeonjeong Ha, Jiayu Liu +10

Recent advances in large language models have led to strong performance on reasoning and environment-interaction tasks, yet their ability for creative problem-solving remains under…

cs.AI2023★ 12 cited

Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration

Zhenhailong Wang, Shaoguang Mao, Wenshan Wu +3

Human intelligence thrives on cognitive synergy, where collaboration among different minds yield superior outcomes compared to isolated individuals. In this work, we propose Solo P…

cs.AI2021

Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification

Zhenhailong Wang, Heng Ji

State-of-the-art brain-to-text systems have achieved great success in decoding language directly from brain signals using neural networks. However, current approaches are limited t…