94 citations · 174 across the 6 of their papers we have counts for
6 papers
ProLLaMA: A Protein Large Language Model for Multi-Task Protein Language Processing
Liuzhenghao Lv, Zongying Lin, Hao Li +5
Recent advances in Protein Language Models (PLMs) have transformed protein engineering, yet unlike their counterparts in Natural Language Processing (NLP), current PLMs exhibit a f…
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models
Bin Lin, Zhenyu Tang, Yang Ye +7
Recent advances demonstrate that scaling Large Vision-Language Models (LVLMs) effectively improves downstream task performances. However, existing scaling methods enable all model…
Machine Mindset: An MBTI Exploration of Large Language Models
Jiaxi Cui, Liuzhenghao Lv, Jing Wen +4
We present a novel approach for integrating Myers-Briggs Type Indicator (MBTI) personality traits into large language models (LLMs), addressing the challenges of personality consis…
Video-Bench: A Comprehensive Benchmark and Toolkit for Evaluating Video-based Large Language Models
Munan Ning, Bin Zhu, Yujia Xie +5
Video-based large language models (Video-LLMs) have been recently introduced, targeting both fundamental improvements in perception and comprehension, and a diverse range of user i…
LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment
Bin Zhu, Bin Lin, Munan Ning +11
The video-language (VL) pretraining has achieved remarkable improvement in multiple downstream tasks. However, the current VL pretraining framework is hard to extend to multiple mo…
Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture
Jiaxi Cui, Munan Ning, Zongjian Li +6
Artificial Intelligence (AI) holds great potential in legal services, yet Large Language Models (LLMs) face two major challenges: limited knowledge of the Chinese legal system and…