4 citations · 6 across the 13 of their papers we have counts for
13 papers
From Solver to Tutor: Evaluating the Pedagogical Intelligence of LLMs with KMP-Bench
Weikang Shi, Houxing Ren, Junting Pan +8
Large Language Models (LLMs) show significant potential in AI mathematical tutoring, yet current evaluations often rely on simplistic metrics or narrow pedagogical scenarios, faili…
WebGen-Agent: Enhancing Interactive Website Generation with Multi-Level Feedback and Step-Level Reinforcement Learning
Zimu Lu, Houxing Ren, Yunqiao Yang +5
Agent systems powered by large language models (LLMs) have demonstrated impressive performance on repository-level code-generation tasks. However, for tasks such as website codebas…
Alignment with Fill-In-the-Middle for Enhancing Code Generation
Houxing Ren, Zimu Lu, Weikang Shi +7
The code generation capabilities of Large Language Models (LLMs) have advanced applications like tool invocation and problem-solving. However, improving performance in code-related…
Probability-Consistent Preference Optimization for Enhanced LLM Reasoning
Yunqiao Yang, Houxing Ren, Zimu Lu +6
Recent advances in preference optimization have demonstrated significant potential for improving mathematical reasoning capabilities in large language models (LLMs). While current…
MathCoder-VL: Bridging Vision and Code for Enhanced Multimodal Mathematical Reasoning
Ke Wang, Junting Pan, Linda Wei +8
Natural language image-caption datasets, widely used for training Large Multimodal Models, mainly focus on natural scenarios and overlook the intricate details of mathematical figu…
SpiritSight Agent: Advanced GUI Agent with One Look
Zhiyuan Huang, Ziming Cheng, Junting Pan +2
Graphical User Interface (GUI) agents show amazing abilities in assisting human-computer interaction, automating human user's navigation on digital devices. An ideal GUI agent is e…
Navi-plus: Managing Ambiguous GUI Navigation Tasks with Follow-up Questions
Ziming Cheng, Zhiyuan Huang, Junting Pan +2
Graphical user interfaces (GUI) automation agents are emerging as powerful tools, enabling humans to accomplish increasingly complex tasks on smart devices. However, users often in…
MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code
Zimu Lu, Aojun Zhou, Ke Wang +5
Code has been shown to be effective in enhancing the mathematical reasoning abilities of large language models due to its precision and accuracy. Previous works involving continued…
Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical Reasoning
Zimu Lu, Aojun Zhou, Ke Wang +5
Direct Preference Optimization (DPO) has proven effective at improving the performance of large language models (LLMs) on downstream tasks such as reasoning and alignment. In this…
ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation
Houxing Ren, Mingjie Zhan, Zhongyuan Wu +3
Code generation plays a crucial role in various tasks, such as code auto-completion and mathematical reasoning. Previous work has proposed numerous methods to enhance code generati…
Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset
Ke Wang, Junting Pan, Weikang Shi +3
Recent advancements in Large Multimodal Models (LMMs) have shown promising results in mathematical reasoning within visual contexts, with models approaching human-level performance…
MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs
Zimu Lu, Aojun Zhou, Houxing Ren +5
Large language models (LLMs) have exhibited great potential in mathematical reasoning. However, there remains a performance gap in this area between existing open-source models and…
TeacherLM: Teaching to Fish Rather Than Giving the Fish, Language Modeling Likewise
Nan He, Hanyu Lai, Chenyang Zhao +12
Large Language Models (LLMs) exhibit impressive reasoning and data augmentation capabilities in various NLP tasks. However, what about small models? In this work, we propose Teache…