15 papers
FinCUABuild: Can Agents Build Reliable Benchmarks for Dynamic Financial Computer Use?
Jingpu Yang, Fengxian Ji, Jinri Guo +7
Financial scenarios are diverse and complex, spanning varying data conditions, tool configurations, and workflows. Yet existing CUA, Computer-Using Agent, evaluation tasks remain l…
Style Wins, Substance Loses: A Diagnosis of LLM-as-Judge in Idea Generation
Fengxian Ji, Yuke Li, Jingpu Yang +8
However, whether these judges truly evaluate the scientific substance of ideas or are influenced by superficial stylistic presentation remains an open question. To address this que…
LabGuard: Grounding Natural-Language Laboratory Rules into Runtime Guards for Embodied Laboratory Agents
Jingpu Yang, Fengxian Ji, Zhengzhao Lai +8
Scientific embodied agents are increasingly capable of carrying out laboratory procedures, but executing these procedures safely in dynamic laboratory environments remains challeng…
OmniFood-Bench: Evaluating VLMs for Nutrient Reasoning and Personalized Health Advice
Qian Jiang, Zhecheng Shi, Jingpu Yang +2
The rapid integration of Large Vision-Language Models (VLMs) into critical infrastructure promises to revolutionize personalized healthcare and dietary management. However, in the…
Parametric Memory Decoding for Zero-Shot Routing in LoRA-Based External Parametric Memory
Fengxian Ji, Zhuohan Xie, Jingpu Yang +3
With the rise of parametric memory, LoRA-based External Parametric Memory (EPM) has emerged as a modular solution, but existing routing methods often introduce additional training,…
TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards
Mingxuan Cui, Jingpu Yang, Fengxian Ji +7
Faithful text rendering remains a persistent weakness of large text-to-image generative models, as it requires both semantic instruction following and fine-grained glyph-level stru…
From Reach to Insert: Tactile-Augmented Precision Assembly under Sub-Millimeter Tolerances
Xinpan Meng, Siyao Huang, JingPu Yang +6
High-precision assembly frequently involves tight-tolerance insertions, where even slight pose errors can cause jamming or excessive interaction forces, making robust and safe inse…
FineState-Bench: Benchmarking State-Conditioned Grounding for Fine-grained GUI State Setting
Fengxian Ji, Jingpu Yang, Zirui Song +5
Despite the rapid progress of large vision-language models (LVLMs), fine-grained, state-conditioned GUI interaction remains challenging. Current evaluations offer limited coverage,…
ServImage: An Image Generation and Editing Benchmark from Real-world Commercial Imaging Services
Fengxian Ji, Jingpu Yang, Zirui Song +5
Recent image generation and editing models demonstrate robust adherence to instructions and high visual quality on academic benchmarks. However, their performance on paid, real-wor…
FineState-Bench: A Comprehensive Benchmark for Fine-Grained State Control in GUI Agents
Fengxian Ji, Jingpu Yang, Zirui Song +6
With the rapid advancement of generative artificial intelligence technology, Graphical User Interface (GUI) agents have demonstrated tremendous potential for autonomously managing…
Frequency Point Game Environment for UAVs via Expert Knowledge and Large Language Model
Jingpu Yang, Hang Zhang, Fengxian Ji +4
Unmanned Aerial Vehicles (UAVs) have made significant advancements in communication stability and security through techniques such as frequency hopping, signal spreading, and adapt…
Agent-Based Anti-Jamming Techniques for UAV Communications in Adversarial Environments: A Comprehensive Survey
Jingpu Yang, Mingxuan Cui, Hang Zhang +3
Unmanned Aerial Vehicle communications are encountering increasingly severe multi-source interference challenges in dynamic adversarial environments, which impose higher demands on…
Geolocation with Real Human Gameplay Data: A Large-Scale Dataset and Human-Like Reasoning Framework
Zirui Song, Jingpu Yang, Yuan Huang +6
Geolocation, the task of identifying an image's location, requires complex reasoning and is crucial for navigation, monitoring, and cultural preservation. However, current methods…
Asynchronous and Segmented Bidirectional Encoding for NMT
Jingpu Yang, Zehua Han, Mengyu Xiang +3
With the rapid advancement of Neural Machine Translation (NMT), enhancing translation efficiency and quality has become a focal point of research. Despite the commendable performan…
Efficient Reinforcement Learning via Decoupling Exploration and Utilization
Jingpu Yang, Helin Wang, Qirui Zhao +3
Reinforcement Learning (RL), recognized as an efficient learning approach, has achieved remarkable success across multiple fields and applications, including gaming, robotics, and…