2 citations · 2 across the 5 of their papers we have counts for
8 papers
Self-Improving Agents with World Model Predictive Paths
Haori Lu, Tianyu Gao, Yaoyao Liu +1
Large language model (LLM) agents are increasingly expected to interact with environments and improve their decisions during deployment. However, how anticipating future outcomes a…
AlphaWiSE: Adaptive Weight Interpolation for Continual Multimodal Representation Learning
Sarthak Jain, Qiran Hu, Zhen Zhu +1
Multimodal models such as CLIP learn a shared embedding space for cross-modal retrieval, but continual adaptation to sequentially arriving data can disrupt the cross-modal alignmen…
AC3S: Adaptive Conditioning for 3D-Aware Synthetic Data Generation
Eric Ji, Qiran Hu, Wufei Ma +4
Synthetic data generation has emerged as a powerful tool for improving data scalability in computer vision. Recent diffusion-based pipelines have demonstrated strong photorealism.…
How to Teach Large Multimodal Models New Skills
Zhen Zhu, Yiming Gong, Yao Xiao +2
How can we teach large multimodal models (LMMs) new skills without erasing prior abilities? We study sequential fine-tuning on five target skills while monitoring general ability o…
Towards Generalized Routing: Model and Agent Orchestration for Adaptive and Efficient Inference
Xiyu Guo, Shan Wang, Chunfang Ji +6
The rapid advancement of large language models (LLMs) and domain-specific AI agents has greatly expanded the ecosystem of AI-powered services. User queries, however, are highly div…
Learning a Category-level Object Pose Estimator without Pose Annotations
Fengrui Tian, Yaoyao Liu, Adam Kortylewski +4
3D object pose estimation is a challenging task. Previous works always require thousands of object images with annotated poses for learning the 3D pose correspondence, which is lab…
Continual Adversarial Defense
Qian Wang, Hefei Ling, Yingwei Li +3
In response to the rapidly evolving nature of adversarial attacks against visual classifiers, numerous defenses have been proposed to generalize against as many known attacks as po…
Prompt-Based Exemplar Super-Compression and Regeneration for Class-Incremental Learning
Ruxiao Duan, Jieneng Chen, Adam Kortylewski +2
Replay-based methods in class-incremental learning (CIL) have attained remarkable success. Despite their effectiveness, the inherent memory restriction results in saving a limited…