most citedFreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models

7 citations · 12 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG20231 cited

Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL

Yang Yue, Rui Lu, Bingyi Kang +2

The divergence of the Q-value estimation has been a prominent issue in offline RL, where the agent has no access to real dynamics. Traditional beliefs attribute this instability to…

cs.CV20237 cited

FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models

Lihe Yang, Xiaogang Xu, Bingyi Kang +2

Semantic segmentation has witnessed tremendous progress due to the proposal of various advanced network architectures. However, they are extremely hungry for delicate annotations t…

cs.CV202317 cited

BuboGPT: Enabling Visual Grounding in Multi-Modal LLMs

Yang Zhao, Zhijie Lin, Daquan Zhou +3

LLMs have demonstrated remarkable abilities at interacting with humans through language, especially with the usage of instruction-following data. Recent advancements in LLMs, such…

cs.LG20231 cited

Improving and Benchmarking Offline Reinforcement Learning Algorithms

Bingyi Kang, Xiao Ma, Yirui Wang +2

Recently, Offline Reinforcement Learning (RL) has achieved remarkable progress with the emergence of various algorithms and datasets. However, these methods usually focus on algori…

cs.CL20233 cited

Bag of Tricks for Training Data Extraction from Language Models

Weichen Yu, Tianyu Pang, Qian Liu +5

With the advance of language models, privacy protection is receiving more attention. Training data extraction is therefore of great importance, as it can serve as a potential tool…