7 citations · 19 across the 14 of their papers we have counts for
16 papers
Evaluating Multi-Turn Multimodal Diagnostic Reasoning on Challenging Real-World Clinical Cases
Rui Yang, Weihao Xuan, Yi Lin +23
Clinical diagnostic evaluation should not only assess whether models can provide correct diagnoses, but also reflect the realities of clinical practice, including progressive discl…
On the Generalization Capacities of MLLMs for Spatial Intelligence
Gongjie Zhang, Wenhao Li, Quanhao Qian +4
Multimodal Large Language Models (MLLMs) that directly process RGB inputs for tasks like 3D localization and navigation have shown remarkable potential. However, we argue that thes…
R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization
Jingyi Zhang, Jiaxing Huang, Huanjin Yao +4
Recent studies generally enhance MLLMs' reasoning capabilities via supervised fine-tuning on high-quality chain-of-thought reasoning data, which often leads models to merely imitat…
MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation
Weihao Xuan, Rui Yang, Heli Qi +29
Existing large language model (LLM) evaluation benchmarks primarily focus on English, while current multilingual tasks lack parallel questions that specifically assess cross-lingui…
Open-Vocabulary Object Detection via Language Hierarchy
Jiaxing Huang, Jingyi Zhang, Kai Jiang +1
Recent studies on generalizable object detection have attracted increasing attention with additional weak supervision from large-scale datasets with image-level labels. However, we…
Historical Test-time Prompt Tuning for Vision Foundation Models
Jingyi Zhang, Jiaxing Huang, Xiaoqin Zhang +2
Test-time prompt tuning, which learns prompts online with unlabelled test samples during the inference stage, has demonstrated great potential by learning effective prompts on-the-…
The Curse of Multi-Modalities: Evaluating Hallucinations of Large Multimodal Models across Language, Visual, and Audio
Sicong Leng, Yun Xing, Zesen Cheng +7
Recent advancements in large multimodal models (LMMs) have significantly enhanced performance across diverse tasks, with ongoing efforts to further integrate additional modalities…
LongHalQA: Long-Context Hallucination Evaluation for MultiModal Large Language Models
Han Qiu, Jiaxing Huang, Peng Gao +4
Hallucination, a phenomenon where multimodal large language models~(MLLMs) tend to generate textual responses that are plausible but unaligned with the image, has become one major…
Foundation Models for Remote Sensing and Earth Observation: A Survey
Aoran Xiao, Weihao Xuan, Junjue Wang +4
Remote Sensing (RS) is a crucial technology for observing, monitoring, and interpreting our planet, with broad applications across geoscience, economics, humanitarian fields, etc.…
Masked AutoDecoder is Effective Multi-Task Vision Generalist
Han Qiu, Jiaxing Huang, Peng Gao +3
Inspired by the success of general-purpose models in NLP, recent studies attempt to unify different vision tasks in the same sequence format and employ autoregressive Transformers…
LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors
Sheng Jin, Xueying Jiang, Jiaxing Huang +2
Inspired by the outstanding zero-shot capability of vision language models (VLMs) in image classification tasks, open-vocabulary object detection has attracted increasing interest…
Learning to Prompt Segment Anything Models
Jiaxing Huang, Kai Jiang, Jingyi Zhang +4
Segment Anything Models (SAMs) like SEEM and SAM have demonstrated great potential in learning to segment anything. The core design of SAMs lies with Promptable Segmentation, which…
DA-BEV: Unsupervised Domain Adaptation for Bird's Eye View Perception
Kai Jiang, Jiaxing Huang, Weiying Xie +3
Camera-only Bird's Eye View (BEV) has demonstrated great potential in environment perception in a 3D space. However, most existing studies were conducted under a supervised setup w…
Domain Adaptation for Large-Vocabulary Object Detectors
Kai Jiang, Jiaxing Huang, Weiying Xie +4
Large-vocabulary object detectors (LVDs) aim to detect objects of many categories, which learn super objectness features and can locate objects accurately while applied to various…
Visual Instruction Tuning towards General-Purpose Multimodal Model: A Survey
Jiaxing Huang, Jingyi Zhang, Kai Jiang +2
Traditional computer vision generally solves each single task independently by a dedicated model with the task instruction implicitly designed in the model architecture, arising tw…
Domain Generalization via Balancing Training Difficulty and Model Capability
Xueying Jiang, Jiaxing Huang, Sheng Jin +1
Domain generalization (DG) aims to learn domain-generalizable models from one or multiple source domains that can perform well in unseen target domains. Despite its recent progress…