28 citations · 73 across the 31 of their papers we have counts for
16 papers · 1 filter
One Rollout Is All You Get: Fully Test-Time Adaptation for GUI Agents
Ziqiang Wang, Li Gu, Zhixiang Chi +6
GUI agents are deployed with frozen weights and discard everything they experience on the job. Existing ways to update an agent's weights assume something deployment withholds: gro…
From Visual Widgets to UI Code: Efficient Tool-Grounded Generation
Houston H. Zhang, Tao Zhang, Li Gu +5
Existing screenshot-to-code systems face a trade-off between flexibility and controllability. Direct multimodal generation can hallucinate visible details, whereas structured pipel…
CoAdapt-GUI: Joint Workflow Context and Policy Adaptation for Unseen GUI Applications
Linqiang Guo, Li Gu, Zihuan Jiang +8
Mobile GUI agents remain brittle when deployed to applications absent from source training. We study novel-app generalization under a limited target interaction budget and without…
Benchmarking LLM Judges for Mobile Agent Evaluation
Ziqiang Wang, Li Gu, Zhixiang Chi +4
Mobile agent benchmarks increasingly rely on LLM-based judges to evaluate task completion, yet the reliability of these judges on mobile agent trajectories remains largely unexamin…
DA-MergeLoRA: Hypernetwork-Based LoRA Merging for Few-Shot Test-Time Domain Adaptation
Siobhan Reid, Zhixiang Chi, Li Gu +3
Few-shot Test-Time Domain Adaptation (FSTT-DA) seeks to adapt models to novel domains using only a handful of unlabeled target samples. This setting is more realistic than typical…
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…
No Adaptation Without Observation: Observability-Constrained Test-Time Prompt Tuning for LiDAR Semantic Segmentation
Linlian Jiang, Wentao Ju, Sadman Rakib Pinon +4
LiDAR semantic segmentation often degrades under real-world deployment due to evolving sensing conditions, while collecting new annotations for retraining is impractical. Test-time…
X-Palm: Paired Multispectral-to-Smartphone Dataset for Cross-Domain Palmprint Authentication
Jamal Seyedmohammadi, Pai Chet Ng, Angelo Genovese +3
Palmprint modality offers a privacy-preserving biometric solution, yet its deployment is hindered by the domain gap between controlled enrollment and unconstrained authentication.…
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…
PACO: Proxy-Task Alignment and Online Calibration for On-the-Fly Category Discovery
Weidong Tang, Bohan Zhang, Zhixiang Chi +3
On-the-Fly Category Discovery (OCD) requires a model, trained on an offline support set, to recognize known classes while discovering new ones from an online streaming sequence. Ex…
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…
Learning through Creation: A Hash-Free Framework for On-the-Fly Category Discovery
Bohan Zhang, Weidong Tang, Zhixiang Chi +4
On-the-Fly Category Discovery (OCD) aims to recognize known classes while simultaneously discovering emerging novel categories during inference, using supervision only from known c…
TALON: Test-time Adaptive Learning for On-the-Fly Category Discovery
Yanan Wu, Yuhan Yan, Tailai Chen +5
On-the-fly category discovery (OCD) aims to recognize known categories while simultaneously discovering novel ones from an unlabeled online stream, using a model trained only on la…
Generalization in Online Reinforcement Learning for Mobile Agents
Li Gu, Zihuan Jiang, Zhixiang Chi +5
Graphical user interface (GUI)-based mobile agents automate digital tasks on mobile devices by interpreting natural-language instructions and interacting with the screen. While rec…
ASMIL: Attention-Stabilized Multiple Instance Learning for Whole Slide Imaging
Linfeng Ye, Shayan Mohajer Hamidi, Zhixiang Chi +5
Attention-based multiple instance learning (MIL) has emerged as a powerful framework for whole slide image (WSI) diagnosis, leveraging attention to aggregate instance-level feature…
Normalized Conditional Mutual Information Surrogate Loss for Deep Neural Classifiers
Linfeng Ye, Zhixiang Chi, Konstantinos N. Plataniotis +1
In this paper, we propose a novel information theoretic surrogate loss; normalized conditional mutual information (NCMI); as a drop in alternative to the de facto cross-entropy (CE…