3 citations · 3 across the 11 of their papers we have counts for
11 papers
Task-Adaptive Rubrics for GUI Reward Modeling
Tao Xiong, Xavier Hu, Wenkai Wang +6
Recent studies on GUI agents have increasingly focused on outcome reward modeling, which assigns outcome rewards by judging whether an executed trajectory satisfies the success cri…
UI-Mate: Advancing Open-Weight Foundation GUI Agents with In-Context Demonstrations
Zihan Ding, Longxu Dou, Qi Gao +26
Foundation GUI agents can automate complex digital tasks, but deployment is hindered by scarce and biased training data, ambiguous prompts, and unreliable execution. Routine workfl…
DEFINED: A Data-Efficient Computational Framework for Fine-Grained Creativity Assessment in Debate Scenarios
Tongzhou Yu, Mingjia Li, Hong Qian +6
Human creativity has emerged as a critical competency in the era of large language models. Assessing creativity in complex, open-ended environments is a grand challenge in data min…
DeskCraft: Benchmarking Desktop Agents on Professional Workflows and Human-in-the-Loop Collaboration
Wenkai Wang, Tao Xiong, Jingchen Ni +6
Real-world professional desktop workflows in specialized creative and engineering software unfold over long horizons and often require human-in-the-loop coordination, where agents…
Correct When Paired, Wrong When Split: Decoupling and Editing Modality-Specific Neurons in MLLMs
Tingchao Fu, Wenkai Wang, Fanxiao Li +6
Although Knowledge Editing provides an efficient mechanism for updating the knowledge of Multimodal Large Language Models (MLLMs), we find that current paradigms still suffer from…
AlphaContext: An Evolutionary Tree-based Psychometric Context Generator for Creativity Assessment
Yixuan Wang, Yue Huang, Hong Qian +7
Creativity has become a core competence in the era of LLMs and human-AI collaboration, underpinning innovation in real-world problem solving. Crucially, the systematic improvement…
Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding
Wenkai Wang, Xiyun Li, Hongcan Guo +5
Graphical User Interface (GUI) grounding requires mapping natural language instructions to precise pixel coordinates. However, due to visually homogeneous elements and dense layout…
A Novel Differential Feature Learning for Effective Hallucination Detection and Classification
Wenkai Wang, Vincent Lee, Yizhen Zheng
Large language model hallucination represents a critical challenge where outputs deviate from factual accuracy due to distributional biases in training data. While recent investiga…
A Rolling Stone Gathers No Moss: Adaptive Policy Optimization for Stable Self-Evaluation in Large Multimodal Models
Wenkai Wang, Hongcan Guo, Zheqi Lv +1
Self-evaluation, a model's ability to assess the correctness of its own output, is crucial for Large Multimodal Models (LMMs) to achieve self-improvement in multi-turn conversation…
Cascaded Self-Evaluation Augmented Training for Lightweight Multimodal LLMs
Zheqi Lv, Wenkai Wang, Jiawei Wang +2
Efficient Multimodal Large Language Models (EMLLMs) can improve performance through Chain-of-Thought (CoT) reasoning, but they have poor self-evaluation capabilities during the CoT…
MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM Integration
Lai Wei, Wenkai Wang, Xiaoyu Shen +5
In recent advancements, multimodal large language models (MLLMs) have been fine-tuned on specific medical image datasets to address medical visual question answering (Med-VQA) task…