1 citations · 1 across the 8 of their papers we have counts for
9 papers
Learning Multimodal Embeddings with Evidence-Aligned Readout
Zirong Chen, Fuda Ye, Enjun Du +8
Multimodal large language models can expose task-relevant evidence through generation, but producing useful evidence does not by itself determine how it enters a retrieval embeddin…
From Saliency to Discriminability: Rank-Preserving Visual Token Pruning for VLM Rerankers
Siyi Liu, Hanjun Yang, Chenchen Zhang +7
Large vision-language models used as listwise rerankers must jointly process visual tokens from tens of candidates per query, making token pruning essential for practical deploymen…
SnapBench: Benchmarking Snap-and-Ask Multimodal Retrieval for Mobile Interactions
Zirong Chen, Fuda Ye, Kuan Zhang +7
Mobile AI acts as a visual oracle, empowering users to snap a picture of something and ask for information. Snap-and-ask retrieval is now one of the most common entry points for mo…
RePair: Turning Retrieval Failures into Counterfactual Hard Pairs
Siyi Liu, Xiaorong Zhu, Enjun Du +6
Vision-language retrieval with CLIP-style dual encoders achieves strong cross-modal performance, yet practical accuracy often hinges on localized semantic distinctions where top-ra…
EviRank: Structured Relevance Evidence for Multimodal Image Re-ranking
Enjun Du, Siyi Liu, Zirong Chen +8
Real-world image search queries are multimodal and compositional: ``find this shirt in pink'' specifies an entity to retain, an attribute to modify, and context to ignore. Yet exis…
Omni IIE Bench: Benchmarking the Practical Capabilities of Image Editing Models
Yujia Yang, Yuanxiang Wang, Zhenyu Guan +11
While Instruction-based Image Editing (IIE) has achieved significant progress, existing benchmarks pursue task breadth via mixed evaluations. This paradigm obscures a critical fail…
VDE Bench: Evaluating The Capability of Image Editing Models to Modify Visual Documents
Hongzhu Yi, Yujia Yang, Yuanxiang Wang +18
Image editing models can modify visual content through natural language, but editing dense documents requires precise local changes amid tightly coupled text, tables, and layout. W…
FastMTP: Accelerating LLM Inference with Enhanced Multi-Token Prediction
Yuxuan Cai, Xiaozhuan Liang, Xinghua Wang +7
As large language models (LLMs) become increasingly powerful, the sequential nature of autoregressive generation creates a fundamental throughput bottleneck that limits the practic…
ARC-Hunyuan-Video-7B: Structured Video Comprehension of Real-World Shorts
Yuying Ge, Yixiao Ge, Chen Li +15
Real-world user-generated short videos, especially those distributed on platforms such as WeChat Channel and TikTok, dominate the mobile internet. However, current large multimodal…