5 papers
BARE: Towards Bias-Aware and Reasoning-Enhanced One-Tower Visual Grounding
Hongbing Li, Linhui Xiao, Zihan Zhao +4
Visual Grounding (VG), which aims to locate a specific region referred to by expressions, is a fundamental yet challenging task in the multimodal understanding fields. While recent…
ModServe: Modality- and Stage-Aware Resource Disaggregation for Scalable Multimodal Model Serving
Haoran Qiu, Anish Biswas, Zihan Zhao +9
Large multimodal models (LMMs) demonstrate impressive capabilities in understanding images, videos, and audio beyond text. However, efficiently serving LMMs in production environme…
Breaking Thought Patterns: A Multi-Dimensional Reasoning Framework for LLMs
Xintong Tang, Meiru Zhang, Shang Xiao +5
Large language models (LLMs) are often constrained by rigid reasoning processes, limiting their ability to generate creative and diverse responses. To address this, a novel framewo…
A Survey of Large Language Models for Text-Guided Molecular Discovery: from Molecule Generation to Optimization
Ziqing Wang, Kexin Zhang, Zihan Zhao +4
Large language models (LLMs) are introducing a paradigm shift in molecular discovery by enabling text-guided interaction with chemical spaces through natural language, symbolic not…
SEEKR: Selective Attention-Guided Knowledge Retention for Continual Learning of Large Language Models
Jinghan He, Haiyun Guo, Kuan Zhu +3
Continual learning (CL) is crucial for language models to dynamically adapt to the evolving real-world demands. To mitigate the catastrophic forgetting problem in CL, data replay h…