Zobrazeno 1 - 10
of 3 160
pro vyhledávání: '"Hauptmann, P."'
We propose a novel scenario to obtain the correct relic abundance for thermally under-produced dark matter. This scenario utilizes a strongly first-order phase transition at temperature $T_{\rm PT}$ that gives rise to dark matter mass $m$. Freeze-out
Externí odkaz:
http://arxiv.org/abs/2409.02179
Autor:
Cheng, Zebang, Tu, Shuyuan, Huang, Dawei, Li, Minghan, Peng, Xiaojiang, Cheng, Zhi-Qi, Hauptmann, Alexander G.
This paper presents our winning approach for the MER-NOISE and MER-OV tracks of the MER2024 Challenge on multimodal emotion recognition. Our system leverages the advanced emotional understanding capabilities of Emotion-LLaMA to generate high-quality
Externí odkaz:
http://arxiv.org/abs/2408.10500
Autor:
Xu, Chao, Sun, Mingze, Cheng, Zhi-Qi, Wang, Fei, Liu, Yang, Sun, Baigui, Huang, Ruqi, Hauptmann, Alexander
In this paper, we propose a novel framework, Combo, for harmonious co-speech holistic 3D human motion generation and efficient customizable adaption. In particular, we identify that one fundamental challenge as the multiple-input-multiple-output (MIM
Externí odkaz:
http://arxiv.org/abs/2408.09397
Autor:
Cheng, Zhi-Qi, Dong, Yifei, Shi, Aike, Liu, Wei, Hu, Yuzhi, O'Connor, Jason, Hauptmann, Alexander, Whitefoot, Kate
The electric vehicle (EV) battery supply chain's vulnerability to disruptions necessitates advanced predictive analytics. We present SHIELD (Schema-based Hierarchical Induction for EV supply chain Disruption), a system integrating Large Language Mode
Externí odkaz:
http://arxiv.org/abs/2408.05357
Autor:
Guo, Tian, Hauptmann, Emmanuel
Large language models (LLMs) and their fine-tuning techniques have demonstrated superior performance in various language understanding and generation tasks. This paper explores fine-tuning LLMs for stock return forecasting with financial newsflow. In
Externí odkaz:
http://arxiv.org/abs/2407.18103
Autor:
Sivakumar, Nikhil S., Aretz, Joost, Scherb, Sebastian, Mavrič, Marion van Midden, Huijgen, Nora, Kamber, Umut, Wegner, Daniel, Khajetoorians, Alexander A., Rösner, Malte, Hauptmann, Nadine
Scanning tunneling microscopy is the method of choice for characterizing charge density waves by imaging the variation in atomic-scale contrast of the surface. Due to the measurement principle of scanning tunneling microscopy, the electronic and latt
Externí odkaz:
http://arxiv.org/abs/2407.17231
Autor:
Zhu, Xiaoyu, Zhou, Hao, Xing, Pengfei, Zhao, Long, Xu, Hao, Liang, Junwei, Hauptmann, Alexander, Liu, Ting, Gallagher, Andrew
In this paper, we investigate the use of diffusion models which are pre-trained on large-scale image-caption pairs for open-vocabulary 3D semantic understanding. We propose a novel method, namely Diff2Scene, which leverages frozen representations fro
Externí odkaz:
http://arxiv.org/abs/2407.13642
Knowledge-intensive visual question answering requires models to effectively use external knowledge to help answer visual questions. A typical pipeline includes a knowledge retriever and an answer generator. However, a retriever that utilizes local i
Externí odkaz:
http://arxiv.org/abs/2407.12277
Autor:
Miller, Matthias, Fürst, Daniel, Fischer, Maximilian T., Hauptmann, Hanna, Keim, Daniel, El-Assady, Mennatallah
Manual melody detection is a tedious task requiring high expertise level, while automatic detection is often not expressive or powerful enough. Thus, we present MelodyVis, a visual application designed in collaboration with musicology experts to expl
Externí odkaz:
http://arxiv.org/abs/2407.05427
Autor:
He, Jun-Yan, Cheng, Zhi-Qi, Li, Chenyang, Sun, Jingdong, He, Qi, Xiang, Wangmeng, Chen, Hanyuan, Lan, Jin-Peng, Lin, Xianhui, Zhu, Kang, Luo, Bin, Geng, Yifeng, Xie, Xuansong, Hauptmann, Alexander G.
MetaDesigner revolutionizes artistic typography synthesis by leveraging the strengths of Large Language Models (LLMs) to drive a design paradigm centered around user engagement. At the core of this framework lies a multi-agent system comprising the P
Externí odkaz:
http://arxiv.org/abs/2406.19859