23 citations · 37 across the 23 of their papers we have counts for
25 papers
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Empowering Character-level Text Infilling by Eliminating Sub-Tokens
Houxing Ren, Mingjie Zhan, Zhongyuan Wu +1
In infilling tasks, sub-tokens, representing instances where a complete token is segmented into two parts, often emerge at the boundaries of prefixes, middles, and suffixes. Tradit…
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…
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…
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…
Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval
Shengyao Zhuang, Linjun Shou, Jian Pei +4
Current dense retrievers (DRs) are limited in their ability to effectively process misspelled queries, which constitute a significant portion of query traffic in commercial search…
Empowering Dual-Encoder with Query Generator for Cross-Lingual Dense Retrieval
Houxing Ren, Linjun Shou, Ning Wu +2
In monolingual dense retrieval, lots of works focus on how to distill knowledge from cross-encoder re-ranker to dual-encoder retriever and these methods achieve better performance…
Lexicon-Enhanced Self-Supervised Training for Multilingual Dense Retrieval
Houxing Ren, Linjun Shou, Jian Pei +3
Recent multilingual pre-trained models have shown better performance in various multilingual tasks. However, these models perform poorly on multilingual retrieval tasks due to lack…
Self-supervised Trajectory Representation Learning with Temporal Regularities and Travel Semantics
Jiawei Jiang, Dayan Pan, Houxing Ren +3
Trajectory Representation Learning (TRL) is a powerful tool for spatial-temporal data analysis and management. TRL aims to convert complicated raw trajectories into low-dimensional…
Unsupervised Context Aware Sentence Representation Pretraining for Multi-lingual Dense Retrieval
Ning Wu, Yaobo Liang, Houxing Ren +4
Recent research demonstrates the effectiveness of using pretrained language models (PLM) to improve dense retrieval and multilingual dense retrieval. In this work, we present a sim…
Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation
Shengyao Zhuang, Houxing Ren, Linjun Shou +4
The Differentiable Search Index (DSI) is an emerging paradigm for information retrieval. Unlike traditional retrieval architectures where index and retrieval are two different and…