1 citations · 3 across the 13 of their papers we have counts for
14 papers · 1 filter
DICS: Exploring Data Intrinsic Consistency for Visual Instruction Selection
Yuyang Hong, Jinhui Guo, Jiaqi Gu +6
Visual instruction tuning is crucial for advancing the vision-language alignment and instruction-following capabilities of Vision-Language Models (VLMs). However, identifying optim…
CC-VQA: Conflict- and Correlation-Aware Method for Mitigating Knowledge Conflict in Knowledge-Based Visual Question Answering
Yuyang Hong, Jiaqi Gu, Yujin Lou +7
Knowledge-based visual question answering (KB-VQA) demonstrates significant potential for handling knowledge-intensive tasks. However, conflicts arise between static parametric kno…
Sketch-in-Latents: Eliciting Unified Reasoning in MLLMs
Jintao Tong, Jiaqi Gu, Yujing Lou +5
While Multimodal Large Language Models (MLLMs) excel at visual understanding tasks through text reasoning, they often fall short in scenarios requiring visual imagination. Unlike c…
NoPe-NeRF++: Local-to-Global Optimization of NeRF with No Pose Prior
Dongbo Shi, Shen Cao, Bojian Wu +5
In this paper, we introduce NoPe-NeRF++, a novel local-to-global optimization algorithm for training Neural Radiance Fields (NeRF) without requiring pose priors. Existing methods,…
Knowledge-based Visual Question Answer with Multimodal Processing, Retrieval and Filtering
Yuyang Hong, Jiaqi Gu, Qi Yang +6
Knowledge-based visual question answering (KB-VQA) requires visual language models (VLMs) to integrate visual understanding with external knowledge retrieval. Although retrieval-au…
SD-VLM: Spatial Measuring and Understanding with Depth-Encoded Vision-Language Models
Pingyi Chen, Yujing Lou, Shen Cao +6
While vision language models (VLMs) excel in 2D semantic visual understanding, their ability to quantitatively reason about 3D spatial relationships remains under-explored, due to…