4 papers · 1 filter
SOLO: A Single Transformer for Scalable Vision-Language Modeling
Yangyi Chen, Xingyao Wang, Hao Peng +1
We present SOLO, a single transformer for Scalable visiOn-Language mOdeling. Current large vision-language models (LVLMs) such as LLaVA mostly employ heterogeneous architectures th…
SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales
Tianyang Xu, Shujin Wu, Shizhe Diao +4
Large language models (LLMs) often generate inaccurate or fabricated information and generally fail to indicate their confidence, which limits their broader applications. Previous…
Executable Code Actions Elicit Better LLM Agents
Xingyao Wang, Yangyi Chen, Lifan Yuan +4
Large Language Model (LLM) agents, capable of performing a broad range of actions, such as invoking tools and controlling robots, show great potential in tackling real-world challe…
R-Tuning: Instructing Large Language Models to Say `I Don't Know'
Hanning Zhang, Shizhe Diao, Yong Lin +6
Large language models (LLMs) have revolutionized numerous domains with their impressive performance but still face their challenges. A predominant issue is the propensity for these…