1 citations · 1 across the 20 of their papers we have counts for
21 papers
IndustryForge-27B: A Domain-Enhanced Multimodal Foundation Model for Industrial CAD
Nianchen Deng, Jiaxin Ai, Tao Hu +10
Automating industrial CAD design and manufacturing places distinctive demands on multimodal foundation models: the model must see engineering drawings and 3D geometry screenshots,…
ComAct: Reframing Professional Software Manipulation via COM-as-Action Paradigm
Jiaxin Ai, Tao Hu, Xuemeng Yang +11
Existing computer-use agents remain fundamentally limited in professional software manipulation: GUI-based agents suffer from fragile visual grounding and long-horizon error accumu…
Faithful, Enriched, and Precise: Benchmarking Natural-Science Illustration Generation by T2I models
Yifan Chang, Jiaxin Ai, Jianwen Sun +9
Scientific illustrations are essential tools for communicating research findings, especially in natural science, where they visualize complex concepts and processes. As Text-to-Ima…
IterCAD: An Iterative Multimodal Agent for Visually-Grounded CAD Generation and Editing
Tao Hu, Jiaxin Ai, Licheng Wen +12
Computer-Aided Design is pivotal in modern manufacturing, yet existing automated methods predominantly rely on open-loop, one-shot generation, creating a mismatch with iterative re…
LongCLI-Bench: A Preliminary Benchmark and Study for Long-horizon Agentic Programming in Command-Line Interfaces
Yukang Feng, Jianwen Sun, Zelai Yang +16
Recent advances in AI-assisted programming have empowered agents to execute complex workflows via command-line interfaces, however, existing benchmarks are limited by short task ho…
World Craft: Agentic Framework to Create Visualizable Worlds via Text
Jianwen Sun, Yukang Feng, Kaining Ying +8
Large Language Models (LLMs) motivate generative agent simulation (e.g., AI Town) to create a ``dynamic world'', holding immense value across entertainment and research. However, f…
MeepleLM: A Virtual Playtester Simulating Diverse Subjective Experiences
Zizhen Li, Chuanhao Li, Yibin Wang +7
Recent advancements have expanded the role of Large Language Models in board games from playing agents to creative co-designers. However, a critical gap remains: current systems la…
ProSoftArena: Benchmarking Hierarchical Capabilities of Multimodal Agents in Professional Software Environments
Jiaxin Ai, Yukang Feng, Fanrui Zhang +8
Multimodal agents are making rapid progress on general computer-use tasks, yet existing benchmarks remain largely confined to browsers and basic desktop applications, falling short…
Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection
Fanrui Zhang, Qiang Zhang, Sizhuo Zhou +10
Existing image forgery detection (IFD) methods either exploit low-level, semantics-agnostic artifacts or rely on multimodal large language models (MLLMs) with high-level semantic k…
From Pixels to Paths: A Multi-Agent Framework for Editable Scientific Illustration
Jianwen Sun, Fanrui Zhang, Yukang Feng +6
Scientific illustrations demand both high information density and post-editability. However, current generative models have two major limitations: Frist, image generation models ou…
Closing the Expression Gap in LLM Instructions via Socratic Questioning
Jianwen Sun, Yukang Feng, Yifan Chang +6
A fundamental bottleneck in human-AI collaboration is the ``intention expression gap," the difficulty for humans to effectively convey complex, high-dimensional thoughts to AI. Thi…
InMind: Evaluating LLMs in Capturing and Applying Individual Human Reasoning Styles
Zizhen Li, Chuanhao Li, Yibin Wang +8
LLMs have shown strong performance on human-centric reasoning tasks. While previous evaluations have explored whether LLMs can infer intentions or detect deception, they often over…
MDK12-Bench: A Comprehensive Evaluation of Multimodal Large Language Models on Multidisciplinary Exams
Pengfei Zhou, Xiaopeng Peng, Fanrui Zhang +18
Multimodal large language models (MLLMs), which integrate language and visual cues for problem-solving, are crucial for advancing artificial general intelligence (AGI). However, cu…
Sekai: A Video Dataset towards World Exploration
Zhen Li, Chuanhao Li, Xiaofeng Mao +17
Video generation techniques have made remarkable progress, promising to be the foundation of interactive world exploration. However, existing video generation datasets are not well…
A High-Quality Dataset and Reliable Evaluation for Interleaved Image-Text Generation
Yukang Feng, Jianwen Sun, Chuanhao Li +8
Recent advancements in Large Multimodal Models (LMMs) have significantly improved multimodal understanding and generation. However, these models still struggle to generate tightly…
SridBench: Benchmark of Scientific Research Illustration Drawing of Image Generation Model
Yifan Chang, Yukang Feng, Jianwen Sun +4
Recent years have seen rapid advances in AI-driven image generation. Early diffusion models emphasized perceptual quality, while newer multimodal models like GPT-4o-image integrate…
MDK12-Bench: A Multi-Discipline Benchmark for Evaluating Reasoning in Multimodal Large Language Models
Pengfei Zhou, Fanrui Zhang, Xiaopeng Peng +17
Multimodal reasoning, which integrates language and visual cues into problem solving and decision making, is a fundamental aspect of human intelligence and a crucial step toward ar…
MPBench: A Comprehensive Multimodal Reasoning Benchmark for Process Errors Identification
Zhaopan Xu, Pengfei Zhou, Jiaxin Ai +6
Reasoning is an essential capacity for large language models (LLMs) to address complex tasks, where the identification of process errors is vital for improving this ability. Recent…
ProJudge: A Multi-Modal Multi-Discipline Benchmark and Instruction-Tuning Dataset for MLLM-based Process Judges
Jiaxin Ai, Pengfei Zhou, Zhaopan Xu +8
As multi-modal large language models (MLLMs) frequently exhibit errors when solving scientific problems, evaluating the validity of their reasoning processes is critical for ensuri…
PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models
Zhaopan Xu, Pengfei Zhou, Weidong Tang +7
Multimodal large language models (MLLMs) have achieved remarkable success in vision-language tasks, but their reliance on vast, internet-sourced data raises significant privacy and…
ARMOR: Empowering Multimodal Understanding Model with Interleaved Multimodal Generation Capability
Jianwen Sun, Yukang Feng, Chuanhao Li +7
Unified multimodal understanding and generation have recently received much attention in the area of vision and language. Existing UniMs are designed to simultaneously learn both m…