2 citations · 2 across the 6 of their papers we have counts for
7 papers
Dynamic Neural Graph Encoding of Inference Processes in Deep Weight Space
Di Wu, Huan Liu, Zhixiang Chi +3
The rapid advancements in using neural networks as implicit data representations have attracted significant interest in developing machine learning methods that analyze and process…
Beyond the GUI Paradigm: Do Mobile Agents Need the Phone Screen?
Li Gu, Zihuan Jiang, Linqiang Guo +6
Recent advances in mobile agents are dominated by the GUI paradigm, in which agents perceive UI information and emit screen interactions. However, mobile platforms also expose a co…
ETR: Entropy Trend Reward for Efficient Chain-of-Thought Reasoning
Xuan Xiong, Huan Liu, Li Gu +4
Chain-of-thought (CoT) reasoning improves large language model performance on complex tasks, but often produces excessively long and inefficient reasoning traces. Existing methods…
Plug-in Feedback Self-adaptive Attention in CLIP for Training-free Open-Vocabulary Segmentation
Zhixiang Chi, Yanan Wu, Li Gu +5
CLIP exhibits strong visual-textual alignment but struggle with open-vocabulary segmentation due to poor localization. Prior methods enhance spatial coherence by modifying intermed…
Learning to Adapt Frozen CLIP for Few-Shot Test-Time Domain Adaptation
Zhixiang Chi, Li Gu, Huan Liu +4
Few-shot Test-Time Domain Adaptation focuses on adapting a model at test time to a specific domain using only a few unlabeled examples, addressing domain shift. Prior methods lever…
Adapting to Distribution Shift by Visual Domain Prompt Generation
Zhixiang Chi, Li Gu, Tao Zhong +4
In this paper, we aim to adapt a model at test-time using a few unlabeled data to address distribution shifts. To tackle the challenges of extracting domain knowledge from a limite…
Test-Time Personalization with Meta Prompt for Gaze Estimation
Huan Liu, Julia Qi, Zhenhao Li +4
Despite the recent remarkable achievement in gaze estimation, efficient and accurate personalization of gaze estimation without labels is a practical problem but rarely touched on…