8 citations · 8 across the 3 of their papers we have counts for
6 papers
ScanReason: Empowering 3D Visual Grounding with Reasoning Capabilities
Chenming Zhu, Tai Wang, Wenwei Zhang +2
Although great progress has been made in 3D visual grounding, current models still rely on explicit textual descriptions for grounding and lack the ability to reason human intentio…
MindSearch: Mimicking Human Minds Elicits Deep AI Searcher
Zehui Chen, Kuikun Liu, Qiuchen Wang +4
Information seeking and integration is a complex cognitive task that consumes enormous time and effort. Inspired by the remarkable progress of Large Language Models, recent works a…
Can AI Assistants Know What They Don't Know?
Qinyuan Cheng, Tianxiang Sun, Xiangyang Liu +7
Recently, AI assistants based on large language models (LLMs) show surprising performance in many tasks, such as dialogue, solving math problems, writing code, and using tools. Alt…
EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AI
Tai Wang, Xiaohan Mao, Chenming Zhu +11
In the realm of computer vision and robotics, embodied agents are expected to explore their environment and carry out human instructions. This necessitates the ability to fully und…
Mixed Pseudo Labels for Semi-Supervised Object Detection
Zeming Chen, Wenwei Zhang, Xinjiang Wang +2
While the pseudo-label method has demonstrated considerable success in semi-supervised object detection tasks, this paper uncovers notable limitations within this approach. Specifi…
Evaluating Hallucinations in Chinese Large Language Models
Qinyuan Cheng, Tianxiang Sun, Wenwei Zhang +8
In this paper, we establish a benchmark named HalluQA (Chinese Hallucination Question-Answering) to measure the hallucination phenomenon in Chinese large language models. HalluQA c…