2 citations · 3 across the 16 of their papers we have counts for
24 papers
Muse Glimmer 30B: An On-Device Agentic Model
Arash Ebrahim Abtahizadeh, Muna Aghamelu, Adil Ahmed +327
We introduce Muse Glimmer, an open-source 30B parameter causal language model with perception encoder, purpose-built for autonomous agentic tasks on consumer hardware. Muse Glimmer…
Glance Forcing: Making Bidirectional Diffusion Autoregressive at a Glance
Zhuobai Dong, Junchao Yi, Hu Jian Guo +3
Autoregressive generation underlies real-time, causal video synthesis and is the backbone of video world models. Today's dominant approach distills a bidirectional diffusion model…
LabInstruct: Benchmarking Situated Instructional Video Generation for Lab Procedures
Yuming Fu, Weijia Wu, Jing Chen +5
Self-driving laboratories (SDLs) aim to automate the full experimental loop, from scientific decision-making to physical execution. Ideally, AI-generated plans could be carried out…
ChartJudgeBench: Evaluating LMM Judges for Chart-to-Code Generation
Lijian Wu, Henry Hengyuan Zhao, Zijian Zhang +3
Building strong chart-to-code systems increasingly relies on reinforcement learning, whose effectiveness depends critically on the quality of the reward signal. Large Multimodal Mo…
Planning and Rendering in Concert: DeepFusion of Autoregressive Layouts and Diffusion for Visual Text Generation
Guanqiao Chen, Jingru Tan, Dongxing Mao +5
Generating text-rich images from prompts requires both textual fidelity and the coherent integration of text into the surrounding image. An explicit layout can provide structured g…
VectorHarness: Recovering Editable, Relation-Preserving Structure from Scientific Graphics
Jiahao Tang, Yiren Song, Alex Jinpeng Wang
Converting scientific graphics into editable representations remains a challenging problem for image-to-code generation because of their heterogeneous elements and complex layouts.…
LIBERO-VIFO: Benchmarking the Capability and Safety of Visual Cue Following in Vision-Language-Action Models
Zhengyan Qian, Rui Yan, Alex Jinpeng Wang +1
Visual cues are increasingly adopted to guide robot learning, but whether Vision-Language-Action (VLA) models can reliably follow authorized cues while disregarding unauthorized on…
See2Think: Do Multimodal Models Really Use Intermediate Visual States?
Siyu Yan, Zhuoran Yan, Haiying Xu +10
Multimodal large language models increasingly use sketches, annotations, tools, and intermediate images during reasoning, but it remains unclear whether they truly rely on these vi…
Efficient Frame Selection for Long Videos at Test Time with Attention-Based MLLM Selectors
Yilin Wang, Xiangxi Zheng, Dongxing Mao +6
Understanding long videos with multimodal large language models (MLLMs) requires selecting a compact set of frames from thousands of candidates, yet identifying the right frames se…
DataEvolver: Self-Evolving Multi-Agent Data Construction for Text-Rich Image Generation
Siyu Yan, Yizhen Gao, Yilin Wang +2
Text-rich image generation is one of the most challenging settings in image generation, since models must simultaneously produce visually realistic images and render legible, seman…
TextGround4M: A Prompt-Aligned Dataset for Layout-Aware Text Rendering
Dongxing Mao, Yilin Wang, Linjie Li +2
Despite recent advances in text-to-image generation, models still struggle to accurately render prompt-specified text with correct spatial layout -- especially in multi-span, struc…
FlowInOne:Unifying Multimodal Generation as Image-in, Image-out Flow Matching
Junchao Yi, Rui Zhao, Jiahao Tang +7
Multimodal generation has long been dominated by text-driven pipelines where language dictates vision but cannot reason or create within it. We challenge this paradigm by asking wh…
Glance: Accelerating Diffusion Models with 1 Sample
Zhuobai Dong, Rui Zhao, Songjie Wu +5
Diffusion models have achieved remarkable success in image generation, yet their deployment remains constrained by the heavy computational cost and the need for numerous inference…
VCode: a Multimodal Coding Benchmark with SVG as Symbolic Visual Representation
Kevin Qinghong Lin, Yuhao Zheng, Hangyu Ran +5
Code has emerged as a precise and executable medium for reasoning and action in the agent era. Yet, progress has largely focused on language-centric tasks such as program synthesis…
Exploring a Unified Vision-Centric Contrastive Alternatives on Multi-Modal Web Documents
Yiqi Lin, Alex Jinpeng Wang, Linjie Li +2
Contrastive vision-language models such as CLIP have demonstrated strong performance across a wide range of multimodal tasks by learning from aligned image-text pairs. However, the…
From Charts to Code: A Hierarchical Benchmark for Multimodal Models
Jiahao Tang, Henry Hengyuan Zhao, Lijian Wu +8
We introduce Chart2Code, a new benchmark for evaluating the chart understanding and code generation capabilities of large multimodal models (LMMs). Chart2Code is explicitly designe…
Seeing is Not Reasoning: MVPBench for Graph-based Evaluation of Multi-path Visual Physical CoT
Zhuobai Dong, Junchao Yi, Ziyuan Zheng +5
Understanding the physical world - governed by laws of motion, spatial relations, and causality - poses a fundamental challenge for multimodal large language models (MLLMs). While…
V-MAGE: A Game Evaluation Framework for Assessing Vision-Centric Capabilities in Multimodal Large Language Models
Xiangxi Zheng, Linjie Li, Zhengyuan Yang +5
Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in visual-text processing. However, existing static image-text benchmarks…
Beyond Words: Advancing Long-Text Image Generation via Multimodal Autoregressive Models
Alex Jinpeng Wang, Linjie Li, Zhengyuan Yang +2
Recent advancements in autoregressive and diffusion models have led to strong performance in image generation with short scene text words. However, generating coherent, long-form t…
TextAtlas5M: A Large-scale Dataset for Dense Text Image Generation
Alex Jinpeng Wang, Dongxing Mao, Jiawei Zhang +9
Text-conditioned image generation has gained significant attention in recent years and are processing increasingly longer and comprehensive text prompt. In everyday life, dense and…
Vision-centric Token Compression in Large Language Model
Ling Xing, Alex Jinpeng Wang, Rui Yan +2
Real-world applications are stretching context windows to hundreds of thousand of tokens while Large Language Models (LLMs) swell from billions to trillions of parameters. This dua…
Leveraging Visual Tokens for Extended Text Contexts in Multi-Modal Learning
Alex Jinpeng Wang, Linjie Li, Yiqi Lin +3
Training models with longer in-context lengths is a significant challenge for multimodal model due to substantial GPU memory and computational costs. This exploratory study does no…
Parrot Captions Teach CLIP to Spot Text
Yiqi Lin, Conghui He, Alex Jinpeng Wang +3
Despite CLIP being the foundation model in numerous vision-language applications, the CLIP suffers from a severe text spotting bias. Such bias causes CLIP models to `Parrot' the vi…
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training
Alex Jinpeng Wang, Linjie Li, Kevin Qinghong Lin +5
In the evolution of Vision-Language Pre-training, shifting from short-text comprehension to encompassing extended textual contexts is pivotal. Recent autoregressive vision-language…