3 citations · 5 across the 4 of their papers we have counts for
5 papers
DeepVision-103K: A Visually Diverse, Broad-Coverage, and Verifiable Mathematical Dataset for Multimodal Reasoning
Haoxiang Sun, Lizhen Xu, Bing Zhao +5
Reinforcement Learning with Verifiable Rewards (RLVR) has been shown effective in enhancing the visual reflection and reasoning capabilities of Large Multimodal Models (LMMs). Howe…
Accelerate 3D Object Detection Models via Zero-Shot Attention Key Pruning
Lizhen Xu, Xiuxiu Bai, Xiaojun Jia +2
Query-based methods with dense features have demonstrated remarkable success in 3D object detection tasks. However, the computational demands of these models, particularly with lar…
Redundant Queries in DETR-Based 3D Detection Methods: Unnecessary and Prunable
Lizhen Xu, Zehao Wu, Wenzhao Qiu +4
Query-based models are extensively used in 3D object detection tasks, with a wide range of pre-trained checkpoints readily available online. However, despite their popularity, thes…
Multiple-Choice Questions are Efficient and Robust LLM Evaluators
Ziyin Zhang, Zhaokun Jiang, Lizhen Xu +2
We present GSM-MC, a multiple-choice (MC) dataset constructed by collecting answers and incorrect predictions on GSM8K from 60 open-source models. Through extensive experiments, we…
R-Judge: Benchmarking Safety Risk Awareness for LLM Agents
Tongxin Yuan, Zhiwei He, Lingzhong Dong +9
Large language models (LLMs) have exhibited great potential in autonomously completing tasks across real-world applications. Despite this, these LLM agents introduce unexpected saf…