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This tutorial explores recent advancements in multimodal pretrained and large models, capable of integrating and processing diverse data forms such as text, images, audio, and video. Participants will gain an understanding of the foundational concept
Externí odkaz:
http://arxiv.org/abs/2410.05608
Generative models must ensure both privacy and fairness for Trustworthy AI. While these goals have been pursued separately, recent studies propose to combine existing privacy and fairness techniques to achieve both goals. However, naively combining t
Externí odkaz:
http://arxiv.org/abs/2410.02246
Visually-Rich Documents (VRDs), encompassing elements like charts, tables, and references, convey complex information across various fields. However, extracting information from these rich documents is labor-intensive, especially given their inconsis
Externí odkaz:
http://arxiv.org/abs/2410.01609
Although Large Language Models(LLMs) can generate coherent and contextually relevant text, they often struggle to recognise the intent behind the human user's query. Natural Language Understanding (NLU) models, however, interpret the purpose and key
Externí odkaz:
http://arxiv.org/abs/2408.08144
Automatic Chart Question Answering (ChartQA) is challenging due to the complex distribution of chart elements with patterns of the underlying data not explicitly displayed in charts. To address this challenge, we design a joint multimodal scene graph
Externí odkaz:
http://arxiv.org/abs/2408.04852
Autor:
Research, LG AI, An, Soyoung, Bae, Kyunghoon, Choi, Eunbi, Choi, Stanley Jungkyu, Choi, Yemuk, Hong, Seokhee, Hong, Yeonjung, Hwang, Junwon, Jeon, Hyojin, Jo, Gerrard Jeongwon, Jo, Hyunjik, Jung, Jiyeon, Jung, Yountae, Kim, Euisoon, Kim, Hyosang, Kim, Joonkee, Kim, Seonghwan, Kim, Soyeon, Kim, Sunkyoung, Kim, Yireun, Kim, Youchul, Lee, Edward Hwayoung, Lee, Haeju, Lee, Honglak, Lee, Jinsik, Lee, Kyungmin, Lee, Moontae, Lee, Seungjun, Lim, Woohyung, Park, Sangha, Park, Sooyoun, Park, Yongmin, Seo, Boseong, Yang, Sihoon, Yeen, Heuiyeen, Yoo, Kyungjae, Yun, Hyeongu
We introduce EXAONE 3.0 instruction-tuned language model, the first open model in the family of Large Language Models (LLMs) developed by LG AI Research. Among different model sizes, we publicly release the 7.8B instruction-tuned model to promote ope
Externí odkaz:
http://arxiv.org/abs/2408.03541
In this work, we tackle the problem of long-form video-language grounding (VLG). Given a long-form video and a natural language query, a model should temporally localize the precise moment that answers the query. Humans can easily solve VLG tasks, ev
Externí odkaz:
http://arxiv.org/abs/2408.02336
Visually Rich Documents (VRDs) are essential in academia, finance, medical fields, and marketing due to their multimodal information content. Traditional methods for extracting information from VRDs depend on expert knowledge and manual labor, making
Externí odkaz:
http://arxiv.org/abs/2408.01287
Autor:
Park, Seohyeon, Yoo, Jaewook, Song, Hyeojun, Lee, Hongseung, Lim, Seongbin, Kim, Soyeon, Park, Minah, Kim, Bongjoong, Heo, Keun, Ye, Peide D., Bae, Hagyoul
We have experimentally demonstrated the effectiveness of beta-gallium oxide (beta-Ga2O3) ferroelectric fin field-effect transistors (Fe-FinFETs) for the first time. Atomic layer deposited (ALD) hafnium zirconium oxide (HZO) is used as the ferroelectr
Externí odkaz:
http://arxiv.org/abs/2407.18187
The significance of mental health classification is paramount in contemporary society, where digital platforms serve as crucial sources for monitoring individuals' well-being. However, existing social media mental health datasets primarily consist of
Externí odkaz:
http://arxiv.org/abs/2407.09020