Tootfinder

JEPA-T: Joint-Embedding Predictive Architecture with Text Fusion for Image Generation
Siheng Wan, Zhengtao Yao, Zhengdao Li, Junhao Dong, Yanshu Li, Yikai Li, Linshan Li, Haoyan Xu, Yijiang Li, Zhikang Dong, Huacan Wang, Jifeng Shen
https://arxiv.org/abs/2510.00974

JEPA-T: Joint-Embedding Predictive Architecture with Text Fusion for Image Generation
Modern Text-to-Image (T2I) generation increasingly relies on token-centric architectures that are trained with self-supervision, yet effectively fusing text with visual tokens remains a challenge. We propose \textbf{JEPA-T}, a unified multimodal framework that encodes images and captions into discrete visual and textual tokens, processed by a joint-embedding predictive Transformer. To enhance fusion, we incorporate cross-attention after the feature predictor for conditional denoising while main…

Japanese brewer Asahi delays product launches, halts deliveries after cyberattack https://therecord.media/japan-asahi-delay-cyberattack

Multi-Value-Product Retrieval-Augmented Generation for Industrial Product Attribute Value Identification
Huike Zou, Haiyang Yang, Yindu Su, Liyu Chen, Chengbao Lian, Qingheng Zhang, Shuguang Han, Jufeng Chen
https://arxiv.org/abs/2509.23874

Multi-Value-Product Retrieval-Augmented Generation for Industrial Product Attribute Value Identification
Identifying attribute values from product profiles is a key task for improving product search, recommendation, and business analytics on e-commerce platforms, which we called Product Attribute Value Identification (PAVI) . However, existing PAVI methods face critical challenges, such as cascading errors, inability to handle out-of-distribution (OOD) attribute values, and lack of generalization capability. To address these limitations, we introduce Multi-Value-Product Retrieval-Augmented Generat…

https://www.instagram.com/p/DN7sUvSEQmn/?utm_source=ig_web_copy_link

Jake Adelstein on Instagram: "The Salaryman who once sustained the Japanese economy is a thing of the past. His beloved pomade, Mandom, is no longer. But somewhere in Kansai, Sakamoto Koseido (阪本高生堂), a company with a longstanding history in barber and salon products, is keeping the dream alive. COCK⚡️GREASE can be purchased easily for rockabilly fans, goth rock stars, or the few remaining salarymen with uncontrollable hair who need a no-nonsene gel. Your hair: COCK⚡️GREASE will "Keep it up all day!!" It's XXXTRA HARD. The pomade is pineapple scented. But don't cry tears of joy when you use it; it's water soluble."
77 likes, 2 comments - tokyovice on August 29, 2025: "The Salaryman who once sustained the Japanese economy is a thing of the past. His beloved pomade, Mandom, is no longer. But somewhere in Kansai, Sakamoto Koseido (阪本高生堂), a company with a longstanding history in barber and salon products, is keeping the dream alive. COCK⚡️GREASE can be purchased easily for rockabilly fans, goth rock stars, or the few remaining salarymen with uncontrollable hair who need a no-nonsene gel. Your h…

GSID: Generative Semantic Indexing for E-Commerce Product Understanding
Haiyang Yang, Qinye Xie, Qingheng Zhang, Liyu Chen, Huike Zou, Chengbao Lian, Shuguang Han, Fei Huang, Jufeng Chen, Bo Zheng
https://arxiv.org/abs/2509.23860

GSID: Generative Semantic Indexing for E-Commerce Product Understanding
Structured representation of product information is a major bottleneck for the efficiency of e-commerce platforms, especially in second-hand ecommerce platforms. Currently, most product information are organized based on manually curated product categories and attributes, which often fail to adequately cover long-tail products and do not align well with buyer preference. To address these problems, we propose \textbf{G}enerative \textbf{S}emantic \textbf{I}n\textbf{D}exings (GSID), a data-driven…

Godzilla Day is coming up on November 3, and knowing this in advance gives me time to maybe tidy up the collection to get a good shot by then. We'll see 😂
https://godzilla.com/blogs/news/how-to-celebrate-godzilla-day-2025

How to Celebrate Godzilla Day 2025
More than seven decades after producer Tomoyuki Tanaka, director Ishirō Honda, and special effects master Eiji Tsuburaya first unleashed Godzilla in Japanese theaters on November 3, 1954, the King of the Monsters remains a beloved symbol of imagination and cinematic innovation. Now, after a landmark 70th anniversary ye

Languages Still Left Behind: Toward a Better Multilingual Machine Translation Benchmark
Chihiro Taguchi, Seng Mai, Keita Kurabe, Yusuke Sakai, Georgina Agyei, Soudabeh Eslami, David Chiang
https://arxiv.org/abs/2508.20511

Languages Still Left Behind: Toward a Better Multilingual Machine Translation Benchmark
Multilingual machine translation (MT) benchmarks play a central role in evaluating the capabilities of modern MT systems. Among them, the FLORES+ benchmark is widely used, offering English-to-many translation data for over 200 languages, curated with strict quality control protocols. However, we study data in four languages (Asante Twi, Japanese, Jinghpaw, and South Azerbaijani) and uncover critical shortcomings in the benchmark's suitability for truly multilingual evaluation. Human assessments…

'Muitos adolescentes nem imaginam como é viver com privacidade'
#ia #ai #etica

Redes sociais: 'Muitos adolescentes nem imaginam como é viver com privacidade' - BBC News Brasil
Somente protegendo a privacidade podemos manter a salvo a democracia, afirma Carissa Véliz, especialista da Universidade de Oxford. Um de seus conselhos para os jovens? Lembrar que 'a vida não é digital — mas, sim, analógica'.

Bra debatt i DN om övervakning och lagändringar som försvagar individens skydd och rätt till integritet.
https://www.dn.se/debatt/vem-vagar-protestera-mot-en-kamera-rakt-in-i-sovrummet/

Does Generative Retrieval Overcome the Limitations of Dense Retrieval?
Yingchen Zhang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Yixing Fan, Xueqi Cheng
https://arxiv.org/abs/2509.22116

Does Generative Retrieval Overcome the Limitations of Dense Retrieval?
Generative retrieval (GR) has emerged as a new paradigm in neural information retrieval, offering an alternative to dense retrieval (DR) by directly generating identifiers of relevant documents. In this paper, we theoretically and empirically investigate how GR fundamentally diverges from DR in both learning objectives and representational capacity. GR performs globally normalized maximum-likelihood optimization and encodes corpus and relevance information directly in the model parameters, wher…