activity
20232026
most citedSolving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification

18 citations · 28 across the 21 of their papers we have counts for

collaborators

23 papers

cs.CL2026

MultiTalk: Scaling Full-Duplex Speech Models to Long, Multi-Party, Bilingual Conversation

Ke Wang, Houxing Ren, Zimu Lu +4

End-to-end full-duplex speech models have brought open-source machine conversation closer to human-like interaction, yet existing systems remain limited in two intertwined dimensio…

cs.CL2026

Edit-Based Refinement for Parallel Masked Diffusion Language Models

Houxing Ren, Mingjie Zhan, Zimu Lu +5

Masked diffusion language models enable parallel token generation and offer improved decoding efficiency over autoregressive models. However, their performance degrades significant…

cs.CL2026

Towards Robust Real-World Spreadsheet Understanding with Multi-Agent Multi-Format Reasoning

Houxing Ren, Mingjie Zhan, Zimu Lu +4

Spreadsheets are central to real-world applications such as enterprise reporting, auditing, and scientific data management. Despite their ubiquity, existing large language model ba…

cs.CV2026

MADCrowner: Margin Aware Dental Crown Design with Template Deformation and Refinement

Linda Wei, Chang Liu, Wenran Zhang +9

Dental crown restoration is one of the most common treatment modalities for tooth defect, where personalized dental crown design is critical. While computer-aided design (CAD) syst…

cs.CL2026

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…

cs.SE2026

FullStack-Agent: Enhancing Agentic Full-Stack Web Coding via Development-Oriented Testing and Repository Back-Translation

Zimu Lu, Houxing Ren, Yunqiao Yang +4

Assisting non-expert users to develop complex interactive websites has become a popular task for LLM-powered code agents. However, existing code agents tend to only generate fronte…

cs.CL2026

SlidesGen-Bench: Evaluating Slides Generation via Computational and Quantitative Metrics

Yunqiao Yang, Wenbo Li, Houxing Ren +6

The rapid evolution of Large Language Models (LLMs) has fostered diverse paradigms for automated slide generation, ranging from code-driven layouts to image-centric synthesis. Howe…

cs.CV2025

MathCanvas: Intrinsic Visual Chain-of-Thought for Multimodal Mathematical Reasoning

Weikang Shi, Aldrich Yu, Rongyao Fang +11

While Large Language Models (LLMs) have excelled in textual reasoning, they struggle with mathematical domains like geometry that intrinsically rely on visual aids. Existing approa…

cs.CV2025

CodePlot-CoT: Mathematical Visual Reasoning by Thinking with Code-Driven Images

Chengqi Duan, Kaiyue Sun, Rongyao Fang +10

Recent advances in Large Language Models (LLMs) and Vision Language Models (VLMs) have shown significant progress in mathematical reasoning, yet they still face a critical bottlene…

cs.CL2025

VoiceAssistant-Eval: Benchmarking AI Assistants across Listening, Speaking, and Viewing

Ke Wang, Houxing Ren, Zimu Lu +2

The growing capabilities of large language models and multimodal systems have spurred interest in voice-first AI assistants, yet existing benchmarks are inadequate for evaluating t…

cs.CL2025

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…

cs.CL2025

LM-Searcher: Cross-domain Neural Architecture Search with LLMs via Unified Numerical Encoding

Yuxuan Hu, Jihao Liu, Ke Wang +7

Recent progress in Large Language Models (LLMs) has opened new avenues for solving complex optimization problems, including Neural Architecture Search (NAS). However, existing LLM-…

cs.CL2025

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…

cs.CL2025

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…

cs.CV2025

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…

cs.CV2025

Adaptive Markup Language Generation for Contextually-Grounded Visual Document Understanding

Han Xiao, Yina Xie, Guanxin Tan +12

Visual Document Understanding has become essential with the increase of text-rich visual content. This field poses significant challenges due to the need for effective integration…

cs.CL2025

WebGen-Bench: Evaluating LLMs on Generating Interactive and Functional Websites from Scratch

Zimu Lu, Yunqiao Yang, Houxing Ren +7

LLM-based agents have demonstrated great potential in generating and managing code within complex codebases. In this paper, we introduce WebGen-Bench, a novel benchmark designed to…

cs.CL2024

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…

cs.CL2024

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…

cs.CV2024★ 4 cited

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…

cs.CL2024★ 2 cited

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…

cs.CL2023★ 4 cited

MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning

Ke Wang, Houxing Ren, Aojun Zhou +7

The recently released GPT-4 Code Interpreter has demonstrated remarkable proficiency in solving challenging math problems, primarily attributed to its ability to seamlessly reason…

cs.CL2023★ 18 cited

Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification

Aojun Zhou, Ke Wang, Zimu Lu +8

Recent progress in large language models (LLMs) like GPT-4 and PaLM-2 has brought significant advancements in addressing math reasoning problems. In particular, OpenAI's latest ver…