3 citations · 6 across the 18 of their papers we have counts for
8 papers · 1 filter
TecoPrompt: Temporal-Conservative Prompt Learning for Vision-Language Models
Zeyi Shao, Haowen Hua, Jiaxin Zhang +3
Prompt learning adapts vision-language models, such as CLIP, by adjusting a small set of context tokens. However, under few-shot supervision, even moderate label noise can disrupt…
Evolutionary Soups: Evolving Mixture-of-Experts for Multi-Objective LLM Alignment
Lingxiao Kong, Steffen Staab, Cong Yang +2
Large language models are increasingly required to generate responses that satisfy multiple competing objectives. Since optimal trade-offs depend on both user preferences and input…
Automated Construction of FAIR Digital Object Knowledge Graphs from Flat Cultural Heritage Records
Zeyd Boukhers, Lingxiao Kong, Xenophon Zabulis +1
The FAIR Digital Object (FDO) framework mandates that metadata attribute values be expressed as persistent identifiers (PIDs) wherever possible, to produce a fully machine-actionab…
ICAN-Deploy: Identity-Stable Canary Deployment for Safety-Critical Embodied Agents
Xue Qin, Simin Luan, John See +3
Canary deployment routes a fraction of traffic to a new software version, monitors metrics, and rolls back on regression. Mainstream controllers (Argo Rollouts, Spinnaker, Flagger)…
Governed Capability Evolution: Lifecycle-Time Compatibility Checking and Rollback for AI-Component-Based Systems, with a Proof-of-Concept Evaluation on Embodied Agents
Xue Qin, Simin Luan, John See +3
Systems built from versioned AI components need lifecycle-time governance over how a new module version is admitted, monitored, and withdrawn. Established deployment patterns (cana…
Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge
Zeyd Boukhers, Oya Beyan, Cong Yang +1
Scientific knowledge on the Web is published as passive assertions and cannot decide when to validate evidence, reconcile contradictions, or update confidence as findings accumulat…
Enhancing RL Generalizability in Robotics through SHAP Analysis of Algorithms and Hyperparameters
Lingxiao Kong, Cong Yang, Oya Deniz Beyan +1
Despite significant advances in Reinforcement Learning (RL), model performance remains highly sensitive to algorithm and hyperparameter configurations, while generalization gaps ac…
RSGen: Enhancing Layout-Driven Remote Sensing Image Generation with Diverse Edge Guidance
Xianbao Hou, Yonghao He, Zeyd Boukhers +4
Diffusion models have significantly mitigated the impact of annotated data scarcity in remote sensing (RS). Although recent approaches have successfully harnessed these models to e…