50 citations · 61 across the 5 of their papers we have counts for
5 papers
DeepDive: Advancing Deep Search Agents with Knowledge Graphs and Multi-Turn RL
Rui Lu, Zhenyu Hou, Zihan Wang +6
Augmenting large language models (LLMs) with browsing tools substantially improves their potential as deep search agents to solve complex, real-world tasks. Yet, open LLMs still pe…
ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline
Yifan Xu, Xiao Liu, Xinghan Liu +9
Large language models (LLMs) have shown excellent mastering of human language, but still struggle in real-world applications that require mathematical problem-solving. While many s…
SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models
Dan Zhang, Ziniu Hu, Sining Zhoubian +6
Large Language Models (LLMs) have shown promise in assisting scientific discovery. However, such applications are currently limited by LLMs' deficiencies in understanding intricate…
CogAgent: A Visual Language Model for GUI Agents
Wenyi Hong, Weihan Wang, Qingsong Lv +11
People are spending an enormous amount of time on digital devices through graphical user interfaces (GUIs), e.g., computer or smartphone screens. Large language models (LLMs) such…
CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X
Qinkai Zheng, Xiao Xia, Xu Zou +10
Large pre-trained code generation models, such as OpenAI Codex, can generate syntax- and function-correct code, making the coding of programmers more productive and our pursuit of…