1 citations · 1 across the 15 of their papers we have counts for
20 papers
Interpolated Policy Distillation: A Controllable Continuum Between Off-Policy and On-Policy Distillation
Youxu Shi, Yifan Sun, Dacheng Yin +5
Off-policy and on-policy distillation have traditionally been formulated as separate paradigms, each favoring a different property of distillation trajectories. Teacher-generated (…
WeVisDoc: From Coverage to Capability for Robust End-to-End Document Parsing
Hao Yu, Kang Liu, Linnan Zhao +4
Document parsing converts document images into structured content and requires reliable performance across diverse layouts and acquisition conditions. Yet training corpora are bias…
WeMM-Embedding: WeChat Multi-Modal Embedding Technical Report
Junjie Zhou, Ke Mei, Lei Li +3
Universal multimodal embeddings are becoming a core component of modern AI systems, enabling heterogeneous content to be represented in a shared space for applications such as retr…
PaDoc: Layout-Grounded Parallel Decoding for Document Parsing
Hao Yu, Jiabo Zhan, Kang Liu +8
End-to-end document parsers provide a unified interface, but serialize page layouts and regional contents into one autoregressive sequence. This formulation forces independent regi…
Orca: The World is in Your Mind
Yihao Wang, Yuheng Ji, Mingyu Cao +54
We introduce Orca, an initial instantiation of a general world foundation model. Orca learns a unified world latent space from multimodal world signals and exposes it through multi…
MMAgent-R: Learning to Rerank and Reject for Agentic mRAG
Tao Zhang, Ziqi Zhang, Zongyang Ma +7
Knowledge-based Visual Question Answering (KB-VQA) requires models to retrieve visual entities matching the query image from large-scale encyclopedic knowledge bases and answer rel…
Segmentation before Answering: Pixel Grounding for MLLM Visual Reasoning
Yake Wei, Yuan Wang, Fengyun Rao +2
Recent advancements in Multimodal Large Language Models (MLLMs) have evolved from static perception to interleaved visual-language reasoning, often referred to as ``thinking with i…
Semantic-Enriched Latent Visual Reasoning
Tianrun Xu, Yue Sun, Qixun Wang +8
Multimodal latent-space reasoning aims to replace explicit thinking with images by performing visual reasoning directly in a compact latent space. However, existing approaches larg…
REVERSE: Reinforcing Evidence Verification and Search for Agentic Image geo-localization
Yong Li, Furong Jia, Dacheng Yin +4
Image geo-localization aims to determine where a photograph was taken, a task that often requires more than recognizing visible landmarks. Human experts typically solve it through…
Stage-adaptive Token Selection for Efficient Omni-modal LLMs
Zijie Xin, Jie Yang, Ruixiang Zhao +4
The unified audio-visual understanding capability of omni-modal large language models (om-LLMs) comes at the high cost of processing tens of thousands of visual and audio tokens th…
OmniPro: A Comprehensive Benchmark for Omni-Proactive Streaming Video Understanding
Ruixiang Zhao, Jie Yang, Zijie Xin +4
Omni-proactive streaming video understanding, i.e., autonomously deciding when to speak and what to say from continuous audio-visual streams, is an emerging capability of omni-moda…
WinTok: A Win-Win Hybrid Tokenizer via Decomposing Visual Understanding and Generation with Transferable Tokens
Yiwei Guo, Shaobin Zhuang, Zhipeng Huang +4
Building a unified visual tokenizer is essential for bridging the gap between visual understanding and generation. Yet existing approaches struggle with the inherent conflict betwe…
AdaMem: Adaptive User-Centric Memory for Long-Horizon Dialogue Agents
Shannan Yan, Jingchen Ni, Leqi Zheng +6
Large language model (LLM) agents increasingly rely on external memory to support long-horizon interaction, personalized assistance, and multi-step reasoning. However, existing mem…
Beyond Chain-of-Thought: Rewrite as a Universal Interface for Generative Multimodal Embeddings
Peixi Wu, Ke Mei, Feipeng Ma +15
Multimodal Large Language Models (MLLMs) have emerged as a promising foundation for universal multimodal embeddings. Recent studies have shown that reasoning-driven generative mult…
Learning Cross-View Object Correspondence via Cycle-Consistent Mask Prediction
Shannan Yan, Leqi Zheng, Keyu Lv +7
We study the task of establishing object-level visual correspondence across different viewpoints in videos, focusing on the challenging egocentric-to-exocentric and exocentric-to-e…
D-ORCA: Dialogue-Centric Optimization for Robust Audio-Visual Captioning
Changli Tang, Tianyi Wang, Fengyun Rao +2
Spoken dialogue is a primary source of information in videos; therefore, accurately identifying who spoke what and when is essential for deep video understanding. We introduce D-OR…
ObjEmbed: Towards Universal Multimodal Object Embeddings
Shenghao Fu, Yukun Su, Fengyun Rao +3
Aligning objects with corresponding textual descriptions is a fundamental challenge and a realistic requirement in vision-language understanding. While recent multimodal embedding…
WeDetect: Fast Open-Vocabulary Object Detection as Retrieval
Shenghao Fu, Yukun Su, Fengyun Rao +3
Open-vocabulary object detection aims to detect arbitrary classes via text prompts. Methods without cross-modal fusion layers (non-fusion) offer faster inference by treating recogn…
WeMMU: Enhanced Bridging of Vision-Language Models and Diffusion Models via Noisy Query Tokens
Jian Yang, Dacheng Yin, Xiaoxuan He +6
Recent progress in multimodal large language models (MLLMs) has highlighted the challenge of efficiently bridging pre-trained Vision-Language Models (VLMs) with Diffusion Models. W…
Instruction-augmented Multimodal Alignment for Image-Text and Element Matching
Xinli Yue, JianHui Sun, Junda Lu +6
With the rapid advancement of text-to-image (T2I) generation models, assessing the semantic alignment between generated images and text descriptions has become a significant resear…