9 papers
LEO-VL: Efficient Scene Representation for Scalable 3D Vision-Language Learning
Jiangyong Huang, Xiaojian Ma, Xiongkun Linghu +6
Developing vision-language models (VLMs) capable of understanding 3D scenes has been a longstanding research goal. Despite recent progress, 3D VLMs still struggle with spatial reas…
Towards Unified World Models for Visual Navigation via Memory-Augmented Planning and Foresight
Yifei Dong, Fengyi Wu, Guangyu Chen +9
Enabling embodied agents to imagine future states is essential for robust and generalizable visual navigation. Yet, state-of-the-art systems typically rely on modular designs that…
Emotion-LLaMAv2 and MMEVerse: A New Framework and Benchmark for Multimodal Emotion Understanding
Xiaojiang Peng, Jingyi Chen, Zebang Cheng +11
Understanding human emotions from multimodal signals poses a significant challenge in affective computing and human-robot interaction. While multimodal large language models (MLLMs…
LongCat-Image Technical Report
Meituan LongCat Team, Hanghang Ma, Haoxian Tan +10
We introduce LongCat-Image, a pioneering open-source and bilingual (Chinese-English) foundation model for image generation, designed to address core challenges in multilingual text…
Why We Feel: Breaking Boundaries in Emotional Reasoning with Multimodal Large Language Models
Yuxiang Lin, Jingdong Sun, Zhi-Qi Cheng +7
Most existing emotion analysis emphasizes which emotion arises (e.g., happy, sad, angry) but neglects the deeper why. We propose Emotion Interpretation (EI), focusing on causal fac…
UMETTS: A Unified Framework for Emotional Text-to-Speech Synthesis with Multimodal Prompts
Zhi-Qi Cheng, Xiang Li, Jun-Yan He +4
Emotional Text-to-Speech (E-TTS) synthesis has garnered significant attention in recent years due to its potential to revolutionize human-computer interaction. However, current E-T…