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pro vyhledávání: '"A, See"'
Large Language Models (LLMs) have demonstrated impressive capabilities in complex reasoning tasks. However, they can be easily misled by unfaithful arguments during conversations, even when their original statements are correct. To this end, we inves
Externí odkaz:
http://arxiv.org/abs/2501.01336
In the rapidly evolving field of Artificial Intelligence Generated Content (AIGC), one of the key challenges is distinguishing AI-synthesized images from natural images. Despite the remarkable capabilities of advanced AI generative models in producin
Externí odkaz:
http://arxiv.org/abs/2412.17632
Autor:
Fletcher, J. D., Park, W., See, P., Griffiths, J. P., Jones, G. A. C., Farrer, I., Ritchie, D. A., Sim, H. -S., Kataoka, M.
While ballistic electrons are a key tool for applications in sensing and flying qubits, sub-nanosecond propagation times and complicated interactions make control of ballistic single electrons challenging. Recent experiments have revealed Coulomb col
Externí odkaz:
http://arxiv.org/abs/2412.15789
Hateful meme detection aims to prevent the proliferation of hateful memes on various social media platforms. Considering its impact on social environments, this paper introduces a previously ignored but significant threat to hateful meme detection: b
Externí odkaz:
http://arxiv.org/abs/2412.15503
The increase in global cellphone usage has led to a spike in instant messaging scams, causing extensive socio-economic damage with yearly losses exceeding half a trillion US dollars. These scams pose a challenge to the integrity of justice systems wo
Externí odkaz:
http://arxiv.org/abs/2412.13528
Autor:
Li, Moxin, Zhao, Yong, Deng, Yang, Zhang, Wenxuan, Li, Shuaiyi, Xie, Wenya, Ng, See-Kiong, Chua, Tat-Seng
Although large language models (LLMs) store vast amount of knowledge in their parameters, they still have limitations in the memorization and utilization of certain knowledge, leading to undesired behaviors such as generating untruthful and inaccurat
Externí odkaz:
http://arxiv.org/abs/2412.12472
Autor:
Lau, Gregory Kang Ruey, Hu, Wenyang, Liu, Diwen, Chen, Jizhuo, Ng, See-Kiong, Low, Bryan Kian Hsiang
Large Language Models still encounter substantial challenges in reasoning tasks, especially for smaller models, which many users may be restricted to due to resource constraints (e.g. GPU memory restrictions). Inference-time methods to boost LLM perf
Externí odkaz:
http://arxiv.org/abs/2412.15238
Autor:
Bellotti, S., Petit, P., Jeffers, S. V., Marsden, S. C., Morin, J., Vidotto, A. A., Folsom, C. P., See, V., Nascimento Jr, J. -D. do
The magnetic cycle on the Sun consists of two consecutive 11-yr sunspot cycles and exhibits a polarity reversal around sunspot maximum. Although solar dynamo theories have progressively become more sophisticated, the details as to how the dynamo sust
Externí odkaz:
http://arxiv.org/abs/2412.09365
Training multimodal models requires a large amount of labeled data. Active learning (AL) aim to reduce labeling costs. Most AL methods employ warm-start approaches, which rely on sufficient labeled data to train a well-calibrated model that can asses
Externí odkaz:
http://arxiv.org/abs/2412.09126
To equip artificial intelligence with a comprehensive understanding towards a temporal world, video and 4D panoptic scene graph generation abstracts visual data into nodes to represent entities and edges to capture temporal relations. Existing method
Externí odkaz:
http://arxiv.org/abs/2412.07160