collaborators

11 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.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.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

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.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…