4 papers
Optimizer-Model Consistency: Full Finetuning with the Same Optimizer as Pretraining Forgets Less
Yuxing Liu, Jianyu Wang, Tong Zhang
Optimizers play an important role in both pretraining and finetuning stages when training large language models (LLMs). In this paper, we present an observation that full finetunin…
VidDoS: Universal Denial-of-Service Attack on Video-based Large Language Models
Duoxun Tang, Dasen Dai, Jiyao Wang +3
Video-LLMs are increasingly deployed in safety-critical applications but are vulnerable to Energy-Latency Attacks (ELAs) that exhaust computational resources. Current image-centric…
VL-Cogito: Progressive Curriculum Reinforcement Learning for Advanced Multimodal Reasoning
Ruifeng Yuan, Chenghao Xiao, Sicong Leng +9
Reinforcement learning has proven its effectiveness in enhancing the reasoning capabilities of large language models. Recent research efforts have progressively extended this parad…
Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning
LASA Team, Weiwen Xu, Hou Pong Chan +16
Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in understanding common visual elements, largely due to their large-scale datasets and advanced t…