1 citations · 1 across the 10 of their papers we have counts for
11 papers
Breaking Data Efficiency Dilemma: A Federated and Augmented Learning Framework For Alzheimer's Disease Detection via Speech
Xiao Wei, Bin Wen, Yuqin Lin +5
Early diagnosis of Alzheimer's Disease (AD) is crucial for delaying its progression. While AI-based speech detection is non-invasive and cost-effective, it faces a critical data ef…
Enhancing Open-Vocabulary Object Detection through Multi-Level Fine-Grained Visual-Language Alignment
Tianyi Zhang, Antoine Simoulin, Kai Li +5
Traditional object detection systems are typically constrained to predefined categories, limiting their applicability in dynamic environments. In contrast, open-vocabulary object d…
Ostrakon-VL: Towards Domain-Expert MLLM for Food-Service and Retail Stores
Zhiyong Shen, Gongpeng Zhao, Jun Zhou +10
Multimodal Large Language Models (MLLMs) have recently achieved substantial progress in general-purpose perception and reasoning. Nevertheless, their deployment in Food-Service and…
TiMem: Temporal-Hierarchical Memory Consolidation for Long-Horizon Conversational Agents
Kai Li, Xuanqing Yu, Ziyi Ni +9
Long-horizon conversational agents have to manage ever-growing interaction histories that quickly exceed the finite context windows of large language models (LLMs). Existing memory…
Refine Thought: A Test-Time Inference Method for Embedding Model Reasoning
Guangzhi Wang, Kai Li, Yinghao Jiao +1
We propose RT (Refine Thought), a method that can enhance the semantic reasoning ability of text embedding models. The method obtains the final semantic representation by running m…
VT-LVLM-AR: A Video-Temporal Large Vision-Language Model Adapter for Fine-Grained Action Recognition in Long-Term Videos
Kaining Li, Shuwei He, Zihan Xu
Human action recognition in long-term videos, characterized by complex backgrounds and subtle action differences, poses significant challenges for traditional deep learning models…
Enhancing Supervised Composed Image Retrieval via Reasoning-Augmented Representation Engineering
Jun Li, Hongjian Dou, Zhenyu Zhang +3
Composed Image Retrieval (CIR) presents a significant challenge as it requires jointly understanding a reference image and a modified textual instruction to find relevant target im…
AudioTrust: Benchmarking the Multifaceted Trustworthiness of Audio Large Language Models
Kai Li, Can Shen, Yile Liu +31
The rapid development and widespread adoption of Audio Large Language Models (ALLMs) demand rigorous evaluation of their trustworthiness. However, existing evaluation frameworks ar…
External Knowledge Injection for CLIP-Based Class-Incremental Learning
Da-Wei Zhou, Kai-Wen Li, Jingyi Ning +3
Class-Incremental Learning (CIL) enables learning systems to continuously adapt to evolving data streams. With the advancement of pre-training, leveraging pre-trained vision-langua…
A Course Shared Task on Evaluating LLM Output for Clinical Questions
Yufang Hou, Thy Thy Tran, Doan Nam Long Vu +4
This paper presents a shared task that we organized at the Foundations of Language Technology (FoLT) course in 2023/2024 at the Technical University of Darmstadt, which focuses on…
Rethinking Video-Text Understanding: Retrieval from Counterfactually Augmented Data
Wufei Ma, Kai Li, Zhongshi Jiang +5
Recent video-text foundation models have demonstrated strong performance on a wide variety of downstream video understanding tasks. Can these video-text models genuinely understand…