3 citations · 10 across the 9 of their papers we have counts for
5 papers · 1 filter
Touch100k: A Large-Scale Touch-Language-Vision Dataset for Touch-Centric Multimodal Representation
Ning Cheng, Changhao Guan, Jing Gao +7
Touch holds a pivotal position in enhancing the perceptual and interactive capabilities of both humans and robots. Despite its significance, current tactile research mainly focuses…
Transformer in Touch: A Survey
Jing Gao, Ning Cheng, Bin Fang +1
The Transformer model, initially achieving significant success in the field of natural language processing, has recently shown great potential in the application of tactile percept…
Potential and Limitations of LLMs in Capturing Structured Semantics: A Case Study on SRL
Ning Cheng, Zhaohui Yan, Ziming Wang +6
Large Language Models (LLMs) play a crucial role in capturing structured semantics to enhance language understanding, improve interpretability, and reduce bias. Nevertheless, an on…
Towards Comprehensive Multimodal Perception: Introducing the Touch-Language-Vision Dataset
Ning Cheng, You Li, Jing Gao +3
Tactility provides crucial support and enhancement for the perception and interaction capabilities of both humans and robots. Nevertheless, the multimodal research related to touch…
TransportationGames: Benchmarking Transportation Knowledge of (Multimodal) Large Language Models
Xue Zhang, Xiangyu Shi, Xinyue Lou +4
Large language models (LLMs) and multimodal large language models (MLLMs) have shown excellent general capabilities, even exhibiting adaptability in many professional domains such…