4 citations · 4 across the 4 of their papers we have counts for
4 papers
Improving Large Language Models Function Calling and Interpretability via Guided-Structured Templates
Hy Dang, Tianyi Liu, Zhuofeng Wu +9
Large language models (LLMs) have demonstrated strong reasoning and tool-use capabilities, yet they often fail in real-world tool-interactions due to incorrect parameterization, po…
Language-Image Alignment with Fixed Text Encoders
Jingfeng Yang, Ziyang Wu, Yue Zhao +1
Currently, the most dominant approach to establishing language-image alignment is to pre-train text and image encoders jointly through contrastive learning, such as CLIP and its va…
RRO: LLM Agent Optimization Through Rising Reward Trajectories
Zilong Wang, Jingfeng Yang, Sreyashi Nag +5
Large language models (LLMs) have exhibited extraordinary performance in a variety of tasks while it remains challenging for them to solve complex multi-step tasks as agents. In pr…
GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length
Hongye Jin, Xiaotian Han, Jingfeng Yang +3
The evolving sophistication and intricacies of Large Language Models (LLMs) yield unprecedented advancements, yet they simultaneously demand considerable computational resources an…