activity
20232026
most citedChartX & ChartVLM: A Versatile Benchmark and Foundation Model for Complicated Chart Reasoning

5 citations · 14 across the 20 of their papers we have counts for

collaborators

21 papers

cs.CV2026

Point as Skeleton: Accumulated Point Cloud Enhanced Autoregressive Generation for Closed-Loop Autonomous Driving Simulation

Songbur Wong, Xiaosong Jia, Junqi You +12

Evaluating end-to-end autonomous driving (E2E-AD) remains challenging, as existing driving simulation methods often trade off closed-loop interactivity (e.g., CARLA) and real-world…

cs.LG2026

How Transformers Learn to Plan via Multi-Token Prediction

Jianhao Huang, Zhanpeng Zhou, Renqiu Xia +3

While next-token prediction (NTP) has been the standard objective for training language models, it often struggles to capture global structure in reasoning tasks. Multi-token predi…

cs.LG2026

Milestones over Outcome: Unlocking Geometric Reasoning with Sub-Goal Verifiable Reward

Jianlong Chen, Daocheng Fu, Shengze Xu +6

Multimodal Large Language Models (MLLMs) struggle with complex geometric reasoning, largely because "black box" outcome-based supervision fails to distinguish between lucky guesses…

cs.CV2025

GeoBench: Rethinking Multimodal Geometric Problem-Solving via Hierarchical Evaluation

Yuan Feng, Yue Yang, Xiaohan He +8

Geometric problem solving constitutes a critical branch of mathematical reasoning, requiring precise analysis of shapes and spatial relationships. Current evaluations of geometric…

cs.CV2025

DriveVGGT: Calibration-Constrained Visual Geometry Transformers for Multi-Camera Autonomous Driving

Xiaosong Jia, Yanhao Liu, Yu Hong +5

Feed-forward reconstruction has been progressed rapidly, with the Visual Geometry Grounded Transformer (VGGT) being a notable baseline. However, directly applying VGGT to autonomou…

astro-ph.IM2025★ 1 cited

AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy

Jinghang Shi, Xiaoyu Tang, Yang Huang +4

Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…

cs.AI2025

Beyond Theorem Proving: Formulation, Framework and Benchmark for Formal Problem-Solving

Qi Liu, Xinhao Zheng, Renqiu Xia +3

As a seemingly self-explanatory task, problem-solving has been a significant component of science and engineering. However, a general yet concrete formulation of problem-solving it…

cs.CV2025

Learning Adaptive and Temporally Causal Video Tokenization in a 1D Latent Space

Yan Li, Changyao Tian, Renqiu Xia +7

We propose AdapTok, an adaptive temporal causal video tokenizer that can flexibly allocate tokens for different frames based on video content. AdapTok is equipped with a block-wise…

cs.AI2025

TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving

Daocheng Fu, Jianlong Chen, Renqiu Xia +12

Geometric problem solving (GPS) requires precise multimodal understanding and rigorous, step-by-step logical reasoning. However, developing capable Multimodal Large Language Models…

cs.CL2025

SurveyForge: On the Outline Heuristics, Memory-Driven Generation, and Multi-dimensional Evaluation for Automated Survey Writing

Xiangchao Yan, Shiyang Feng, Jiakang Yuan +4

Survey paper plays a crucial role in scientific research, especially given the rapid growth of research publications. Recently, researchers have begun using LLMs to automate survey…

cs.CV2025

GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-training

Renqiu Xia, Mingsheng Li, Hancheng Ye +12

Despite their proficiency in general tasks, Multi-modal Large Language Models (MLLMs) struggle with automatic Geometry Problem Solving (GPS), which demands understanding diagrams,…

cs.CV2024

Chimera: Improving Generalist Model with Domain-Specific Experts

Tianshuo Peng, Mingsheng Li, Jiakang Yuan +11

Recent advancements in Large Multi-modal Models (LMMs) underscore the importance of scaling by increasing image-text paired data, achieving impressive performance on general tasks.…

cs.CV2024

Training-Free Adaptive Diffusion with Bounded Difference Approximation Strategy

Hancheng Ye, Jiakang Yuan, Renqiu Xia +5

Diffusion models have recently achieved great success in the synthesis of high-quality images and videos. However, the existing denoising techniques in diffusion models are commonl…

cs.CV2024

Image Over Text: Transforming Formula Recognition Evaluation with Character Detection Matching

Bin Wang, Fan Wu, Linke Ouyang +5

Formula recognition presents significant challenges due to the complicated structure and varied notation of mathematical expressions. Despite continuous advancements in formula rec…

cs.CV2024

DocGenome: An Open Large-scale Scientific Document Benchmark for Training and Testing Multi-modal Large Language Models

Renqiu Xia, Song Mao, Xiangchao Yan +19

Scientific documents record research findings and valuable human knowledge, comprising a vast corpus of high-quality data. Leveraging multi-modality data extracted from these docum…

cs.CV2024

Once for Both: Single Stage of Importance and Sparsity Search for Vision Transformer Compression

Hancheng Ye, Chong Yu, Peng Ye +5

Recent Vision Transformer Compression (VTC) works mainly follow a two-stage scheme, where the importance score of each model unit is first evaluated or preset in each submodule, fo…

cs.CV2024★ 5 cited

ChartX & ChartVLM: A Versatile Benchmark and Foundation Model for Complicated Chart Reasoning

Renqiu Xia, Bo Zhang, Hancheng Ye +9

Recently, many versatile Multi-modal Large Language Models (MLLMs) have emerged continuously. However, their capacity to query information depicted in visual charts and engage in r…

cs.CV2023

On the Evaluation and Refinement of Vision-Language Instruction Tuning Datasets

Ning Liao, Shaofeng Zhang, Renqiu Xia +3

There is an emerging line of research on multimodal instruction tuning, and a line of benchmarks has been proposed for evaluating these models recently. Instead of evaluating the m…

cs.CV2023★ 3 cited

StructChart: On the Schema, Metric, and Augmentation for Visual Chart Understanding

Renqiu Xia, Haoyang Peng, Hancheng Ye +7

Charts are common in literature across various scientific fields, conveying rich information easily accessible to readers. Current chart-related tasks focus on either chart percept…

cs.CV2023★ 2 cited

SPOT: Scalable 3D Pre-training via Occupancy Prediction for Learning Transferable 3D Representations

Xiangchao Yan, Runjian Chen, Bo Zhang +11

Annotating 3D LiDAR point clouds for perception tasks is fundamental for many applications e.g., autonomous driving, yet it still remains notoriously labor-intensive. Pretraining-f…

cs.CV2023★ 3 cited

ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation

Bo Zhang, Xinyu Cai, Jiakang Yuan +10

Domain shifts such as sensor type changes and geographical situation variations are prevalent in Autonomous Driving (AD), which poses a challenge since AD model relying on the prev…