3 papers
cs.AI2026
CoVe: Training Interactive Tool-Use Agents via Constraint-Guided Verification
Jinpeng Chen, Cheng Gong, Hanbo Li +9
Developing multi-turn interactive tool-use agents is challenging because real-world user needs are often complex and ambiguous, yet agents must execute deterministic actions to sat…
cs.LG2026
Meta-Learning Hyperparameters for Parameter Efficient Fine-Tuning
Zichen Tian, Yaoyao Liu, Qianru Sun
Training large foundation models from scratch for domain-specific applications is almost impossible due to data limits and long-tailed distributions -- taking remote sensing (RS) a…
cs.LG2026
Scalable Multi-Task Low-Rank Model Adaptation
Zichen Tian, Antoine Ledent, Qianru Sun
Scaling multi-task low-rank adaptation (LoRA) to a large number of tasks induces catastrophic performance degradation, such as an accuracy drop from 88.2% to 2.0% on DOTA when scal…