activity
20242026
collaborators

24 papers

cs.CV2026

Concept-as-Tree: A Controllable Synthetic Data Framework Makes Stronger Personalized VLMs

Ruichuan An, Kai Zeng, Ming Lu +5

Vision-Language Models (VLMs) have demonstrated exceptional performance in various multi-modal tasks. Recently, there has been an increasing interest in improving the personalizati…

cs.CL2026

LatentOmni: Rethinking Omni-Modal Understanding via Unified Audio-Visual Latent Reasoning

Yifan Dai, Zhenhua Wu, Bohan Zeng +18

Joint audio-visual reasoning is essential for omnimodal understanding, yet current multimodal large language models (MLLMs) still struggle when reasoning requires fine-grained evid…

cs.CL2026

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

DeepSeek-AI, Anyi Xu, Bangcai Lin +315

We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…

cs.MM2026

Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction

Qintong Zhang, Bin Wang, Victor Shea-Jay Huang +5

Document parsing (DP) transforms unstructured or semi-structured documents into structured, machine-readable representations, enabling downstream applications such as knowledge bas…

cs.CL2026

Let's Verify Math Questions Step by Step

Chengyu Shen, Zhen Hao Wong, Runming He +8

Large Language Models (LLMs) have recently achieved remarkable progress in mathematical reasoning. To enable such capabilities, many existing works distill strong reasoning models…

cs.AI2026

BrowseComp-: A Visual, Vertical, and Verifiable Benchmark for Multimodal Browsing Agents

Huanyao Zhang, Jiepeng Zhou, Bo Li +22

Multimodal large language models (MLLMs), equipped with increasingly advanced planning and tool-use capabilities, are evolving into autonomous agents capable of performing multimod…