7 citations · 11 across the 24 of their papers we have counts for
7 papers · 1 filter
Deeply Interleaved Text-Image Contexts for Multimodal LLMs Assessment
Zihao Wang, Xi Xiang, Yuwen Sun +5
Current evaluations and training of multimodal models predominantly focus on multi-image tasks, largely overlooking interleaved text-image scenarios. In such multi-image tasks, tex…
LongStraw: Long-Context RL Beyond 2M Tokens under a Fixed GPU Budget
Changhai Zhou, Kieran Liu, Yuhua Zhou +17
Long-context RL post-training is constrained by the lifetime of state and gradients, not attention cost alone. In GRPO, one multi-million-token prompt must serve old-policy and ref…
KEMO: Event-Driven Keyframe Memory for Long-Horizon Robot Manipulation with VLA Policies
Yihan Zeng, Minghao Ye, Yiyuan Chen +4
Long-horizon robot manipulation remains challenging because similar observations may occur at different execution stages, while the appropriate action depends on previously complet…
FedSmoothLoRA: Toward Smoother and Faster Convergence in Federated Low-Rank Adaptation
Zehao Wang, Guanglei Yang, Yihan Zeng +4
Federated fine-tuning of foundation models with Low-Rank Adaptation (LoRA) provides an efficient solution for reducing communication and computation costs while preserving data loc…
AnE: Pushing the Reasoning Frontier of Multimodal LLMs via Anchor Evolution
Zehao Wang, Yihan Zeng, Zidong Gong +5
Post-training via Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) is crucial for enhancing reasoning in Multimodal Large Language Models (MLLMs), yet existing paradigm…
OPERA: An Agent for Image Restoration with End-to-End Joint Planning-Execution Optimization
Feng Zhu, Shuyang Xie, Yihan Zeng +2
Real-world image restoration is challenging due to complex and interacting mixed degradations. Recent agent-based approaches address this problem by composing multiple task-specifi…
CGL: Advancing Continual GUI Learning via Reinforcement Fine-Tuning
Zhenquan Yao, Zitong Huang, Yihan Zeng +5
Graphical User Interface (GUI) Agents, benefiting from recent advances in multimodal large language models (MLLM), have achieved significant development. However, due to the freque…