1 citations · 2 across the 14 of their papers we have counts for
16 papers
Beyond Accuracy: Evaluating Grounded Visual Evidence in Thinking with Images
Xuchen Li, Xuzhao Li, Renjie Pi +3
Despite the remarkable progress of Vision-Language Models (VLMs) in adopting "Thinking-with-Images" capabilities, accurately evaluating the authenticity of their reasoning process…
MATrack: Efficient Multiscale Adaptive Tracker for Real-Time Nighttime UAV Operations
Xuzhao Li, Xuchen Li, Shiyu Hu
Nighttime UAV tracking faces significant challenges in real-world robotics operations. Low-light conditions not only limit visual perception capabilities, but cluttered backgrounds…
Select Less, Reason More: Prioritizing Evidence Purity for Video Reasoning
Xuchen Li, Xuzhao Li, Shiyu Hu +1
Long-form video reasoning remains a major challenge for Video Large Language Models (Video LLMs), as static uniform frame sampling leads to information dilution and obscures critic…
Look Less, Reason More: Rollout-Guided Adaptive Pixel-Space Reasoning
Xuchen Li, Xuzhao Li, Jiahui Gao +3
Vision-Language Models (VLMs) excel at many multimodal tasks, yet they frequently struggle with tasks requiring precise understanding and handling of fine-grained visual elements.…
VS-LLM: Visual-Semantic Depression Assessment based on LLM for Drawing Projection Test
Meiqi Wu, Yaxuan Kang, Xuchen Li +5
The Drawing Projection Test (DPT) is an essential tool in art therapy, allowing psychologists to assess participants' mental states through their sketches. Specifically, through sk…
ATCTrack: Aligning Target-Context Cues with Dynamic Target States for Robust Vision-Language Tracking
X. Feng, S. Hu, X. Li +5
Vision-language tracking aims to locate the target object in the video sequence using a template patch and a language description provided in the initial frame. To achieve robust t…
VerifyBench: A Systematic Benchmark for Evaluating Reasoning Verifiers Across Domains
Xuzhao Li, Xuchen Li, Shiyu Hu +2
Large language models (LLMs) increasingly rely on reinforcement learning (RL) to enhance their reasoning capabilities through feedback. A critical challenge is verifying the consis…
CausalStep: A Benchmark for Explicit Stepwise Causal Reasoning in Videos
Xuchen Li, Xuzhao Li, Shiyu Hu +2
Recent advances in large language models (LLMs) have improved reasoning in text and image domains, yet achieving robust video reasoning remains a significant challenge. Existing vi…
DARTer: Dynamic Adaptive Representation Tracker for Nighttime UAV Tracking
Xuzhao Li, Xuchen Li, Shiyu Hu
Nighttime UAV tracking presents significant challenges due to extreme illumination variations and viewpoint changes, which severely degrade tracking performance. Existing approache…
Enhancing Vision-Language Tracking by Effectively Converting Textual Cues into Visual Cues
X. Feng, D. Zhang, S. Hu +5
Vision-Language Tracking (VLT) aims to localize a target in video sequences using a visual template and language description. While textual cues enhance tracking potential, current…
How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking
Xuchen Li, Shiyu Hu, Xiaokun Feng +4
Vision-language tracking (VLT) extends traditional single object tracking by incorporating textual information, providing semantic guidance to enhance tracking performance under ch…
DTVLT: A Multi-modal Diverse Text Benchmark for Visual Language Tracking Based on LLM
Xuchen Li, Shiyu Hu, Xiaokun Feng +4
Visual language tracking (VLT) has emerged as a cutting-edge research area, harnessing linguistic data to enhance algorithms with multi-modal inputs and broadening the scope of tra…
When LLMs Learn to be Students: The SOEI Framework for Modeling and Evaluating Virtual Student Agents in Educational Interaction
Yiping Ma, Shiyu Hu, Xuchen Li +4
Recent advances in large language models (LLMs) have enabled intelligent tutoring systems, yet the development of LLM-based Virtual Student Agents (LVSAs) remains underexplored. Su…
FIOVA: A Multi-Annotator Benchmark for Human-Aligned Video Captioning
Shiyu Hu, Xuchen Li, Xuzhao Li +4
Despite rapid progress in large vision-language models (LVLMs), existing video caption benchmarks remain limited in evaluating their alignment with human understanding. Most rely o…
Visual Language Tracking with Multi-modal Interaction: A Robust Benchmark
Xuchen Li, Shiyu Hu, Xiaokun Feng +4
Visual Language Tracking (VLT) enhances tracking by mitigating the limitations of relying solely on the visual modality, utilizing high-level semantic information through language.…
DTLLM-VLT: Diverse Text Generation for Visual Language Tracking Based on LLM
Xuchen Li, Xiaokun Feng, Shiyu Hu +4
Visual Language Tracking (VLT) enhances single object tracking (SOT) by integrating natural language descriptions from a video, for the precise tracking of a specified object. By l…