Zobrazeno 1 - 10
of 18 840
pro vyhledávání: '"McAuley AT"'
Autor:
Shimizu, Ryotaro, Wang, Yu, Kimura, Masanari, Hirakawa, Yuki, Wada, Takashi, Saito, Yuki, McAuley, Julian
In this work, we propose a fashion item recommendation model that incorporates hyperbolic geometry into user and item representations. Using hyperbolic space, our model aims to capture implicit hierarchies among items based on their visual data and u
Externí odkaz:
http://arxiv.org/abs/2409.02599
Autor:
Korikov, Anton, Sanner, Scott, Deldjoo, Yashar, He, Zhankui, McAuley, Julian, Ramisa, Arnau, Vidal, Rene, Sathiamoorthy, Mahesh, Kasrizadeh, Atoosa, Milano, Silvia, Ricci, Francesco
While previous chapters focused on recommendation systems (RSs) based on standardized, non-verbal user feedback such as purchases, views, and clicks -- the advent of LLMs has unlocked the use of natural language (NL) interactions for recommendation.
Externí odkaz:
http://arxiv.org/abs/2408.10946
The task of multi-objective alignment aims at balancing and controlling the different alignment objectives (e.g., helpfulness, harmlessness and honesty) of large language models to meet the personalized requirements of different users. However, previ
Externí odkaz:
http://arxiv.org/abs/2408.05094
Customers reach out to online live chat agents with various intents, such as asking about product details or requesting a return. In this paper, we propose the problem of predicting user intent from browsing history and address it through a two-stage
Externí odkaz:
http://arxiv.org/abs/2408.04668
Calibrated recommendation, which aims to maintain personalized proportions of categories within recommendations, is crucial in practical scenarios since it enhances user satisfaction by reflecting diverse interests. However, achieving calibration in
Externí odkaz:
http://arxiv.org/abs/2408.02156
Autor:
Wu, Junda, Li, Xintong, Yu, Tong, Wang, Yu, Chen, Xiang, Gu, Jiuxiang, Yao, Lina, Shang, Jingbo, McAuley, Julian
Instruction tuning in multimodal large language models (MLLMs) aims to smoothly integrate a backbone LLM with a pre-trained feature encoder for downstream tasks. The major challenge is how to efficiently find the synergy through cooperative learning
Externí odkaz:
http://arxiv.org/abs/2407.20454
Autor:
Wu, Junda, Novack, Zachary, Namburi, Amit, Dai, Jiaheng, Dong, Hao-Wen, Xie, Zhouhang, Chen, Carol, McAuley, Julian
Existing music captioning methods are limited to generating concise global descriptions of short music clips, which fail to capture fine-grained musical characteristics and time-aware musical changes. To address these limitations, we propose FUTGA, a
Externí odkaz:
http://arxiv.org/abs/2407.20445
Role-playing has wide-ranging applications in customer support, embodied agents, computational social science, etc. The influence of parametric world knowledge of large language models (LLMs) often causes role-playing characters to act out of charact
Externí odkaz:
http://arxiv.org/abs/2406.17260
Autor:
Appel, Christian, Schmeltz, Margaux, Rodriguez-Fernandez, Irene, Anschuetz, Lukas, Nielsen, Leonard C., Panepucci, Ezequiel, Marijolovic, Tomislav, Wakonig, Klaus, Ivanovic, Aleksandra, Bonnin, Anne, Leonarski, Filip, Wojdyla, Justyna, Tomizaki, Takashi, Guizar-Sicairos, Manuel, Smith, Kate, Beale, John H., Glettig, Wayne, McAuley, Katherine, Bunk, Oliver, Wang, Meitian, Liebi, Marianne
Small Angle-X-ray Scattering Tensor Tomography (SAS-TT) is a relatively new, but powerful technique for studying the multiscale architecture of hierarchical structures, which is of particular interest for life science applications. Currently, the tec
Externí odkaz:
http://arxiv.org/abs/2406.13238
The comparison between Auto-Encoding (AE) and Auto-Regression (AR) has become an increasingly important topic with recent advances in sequential recommendation. At the heart of this discussion lies the comparison of BERT4Rec and SASRec, which serve a
Externí odkaz:
http://arxiv.org/abs/2406.02048