1 citations · 1 across the 8 of their papers we have counts for
10 papers
Heading Hierarchy Reconstruction for Complex and Long Documents with Level-Wise Multimodal Memory
Qian Chen, Xianyin Zhang, Lifan Guo +1
Vision-language models (VLMs) have been widely adopted for document parsing and optical character recognition (OCR), as they can accurately extract page-level elements. However, do…
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs
Qian Chen, Jinlan Fu, Changsong Li +3
Although Multimodal Large Language Models (MLLMs) demonstrate strong omni-modal perception, their ability to forecast future events from audio-visual cues remains largely unexplore…
SAM3-I: Segment Anything with Instructions
Jingjing Li, Yue Feng, Yuchen Guo +10
Segment Anything Model 3 (SAM3) advances open-vocabulary segmentation through promptable concept segmentation, enabling users to segment all instances associated with a given conce…
Distilled Decoding 2: One-step Sampling of Image Auto-regressive Models with Conditional Score Distillation
Enshu Liu, Qian Chen, Xuefei Ning +4
Image Auto-regressive (AR) models have emerged as a powerful paradigm of visual generative models. Despite their promising performance, they suffer from slow generation speed due t…
Shortcutting Pre-trained Flow Matching Diffusion Models is Almost Free Lunch
Xu Cai, Yang Wu, Qianli Chen +3
We present an ultra-efficient post-training method for shortcutting large-scale pre-trained flow matching diffusion models into efficient few-step samplers, enabled by novel veloci…
MEASER: Malware embedding attacks on open-source LLMs
Ming Tan, Wei Li, Hu Tao +4
Open-source large language models (LLMs) have demonstrated considerable dominance over proprietary LLMs in resolving neural processing tasks, thanks to the collaborative and sharin…
DianJin-OCR-R1: Enhancing OCR Capabilities via a Reasoning-and-Tool Interleaved Vision-Language Model
Qian Chen, Xianyin Zhang, Lifan Guo +2
Recent advances in vision-language models (VLMs) have enabled end-to-end document parsing and understanding, achieving strong performance on diverse optical character recognition (…
Runtime Failure Hunting for Physics Engine Based Software Systems: How Far Can We Go?
Shuqing Li, Qiang Chen, Xiaoxue Ren +1
Physics Engines (PEs) are fundamental software frameworks that simulate physical interactions in applications ranging from entertainment to safety-critical systems. Despite their i…
Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks
Qiang Chen, Tianyang Han, Jin Li +5
Can AI effectively perform complex econometric analysis traditionally requiring human expertise? This paper evaluates AI agents' capability to master econometrics, focusing on empi…
DianJin-R1: Evaluating and Enhancing Financial Reasoning in Large Language Models
Jie Zhu, Qian Chen, Huaixia Dou +4
Effective reasoning remains a core challenge for large language models (LLMs) in the financial domain, where tasks often require domain-specific knowledge, precise numerical calcul…