arXiv:2609.25438v1 Announce Type: new
Abstract: Diverse pretraining has been shown to be an effective method for learning reusable, domain-aware representations that provide a starting point for fine...
By Henry Kvinge
arXiv:2609.25602v1 Announce Type: new
Abstract: In language models, the choice between believing the prompt and believing the weights is made by a handful of identifiable attention heads. Instruction...
By Shubham Santosh Pandere, Gautam Ranka, Ritika Varshney, Navya Deshmukh, Roushni Sareen, Roshan Kumar Singh
arXiv:2609.26402v1 Announce Type: new
Abstract: The discovery of novel inorganic materials drives technological breakthroughs in critical fields such as computing and energy storage. Generative AI ha...
By Thomas Egg, Harry Winston Sullivan, Ellad B. Tadmor, Stefano Martiniani
arXiv:2609.26631v1 Announce Type: new
Abstract: Accurate ground-based cloud classification is important for atmospheric monitoring, solar-energy forecasting, aviation weather assessment, and climate...
By Esther Bou Dagher, Viktoriya Bu-Dager, Boguslaw Zegarlinski
arXiv:2601.08358v2 Announce Type: replace
Abstract: Even though the ocean covers the majority of the planet's surface, it remains the least explored ecosystem. As light and radio waves do not propaga...
By Hilde I. Hummel, Sandjai Bhulai, Rob D. van der Mei, Burooj Ghani
arXiv:2605.00126v2 Announce Type: replace
Abstract: Generative models for time-series imputation achieve strong reconstruction accuracy, yet provide no finite-sample reliability guarantees, a critica...
By Arnaud Zinflou
arXiv:2609.26399v1 Announce Type: new
Abstract: Scene safety understanding plays a life-or-death role in situational awareness in various critical domains. Traditional methods that rely on learning d...
By Zhiyun Jiang, Hanyong Wang, Binbin Liang, Yu Xie, Zhengjie Wang, Menglong Yang, Wei Li
arXiv:2609.26185v1 Announce Type: cross
Abstract: Large Language Models (LLMs) demonstrate impressive capabilities across many applications but remain vulnerable to jailbreak attacks, which elicit ha...
By Doniyorkhon Obidov, Honggang Yu, Xiaolong Guo, Kaichen Yang
arXiv:2603.03806v2 Announce Type: replace
Abstract: The state space model Mamba has recently emerged as a promising paradigm in computer vision, attracting considerable attention for its efficient ha...
By Hanpeng Liu, Zidan Wang, Shuoxi Zhang, Kaiyuan Gao, Kun He
arXiv:2605.30263v2 Announce Type: replace
Abstract: Recent video diffusion foundation models have achieved remarkable progress in high-quality video generation, yet turning them into real-time intera...
By Min Zhao, Hongzhou Zhu, Bokai Yan, Zihan Zhou, Yimin Chen, Honglie Wang, Wenqiang Sun, Zhengwei Fang, Zizheng Xun, Zihao Li, Kaiwen Zheng, Guande He, Xiao Yang, Chongxuan Li, Fan Bao, Jun Zhu
arXiv:2609.25722v1 Announce Type: new
Abstract: Signed graphs arise in trust--distrust networks, financial correlation systems, biological interaction graphs, and many other domains in which edges ca...
By Zihan Mei, Rong Pan, Yuzhou Chen, Yixuan He
arXiv:2609.25862v1 Announce Type: new
Abstract: We present the first experiments on isolated sign language recognition (ISLR) for Icelandic Sign Language (\'ITM). We use \'ITM SignWiki, a dataset der...
By Finnur \'Ag\'ust Ingimundarson, Gu{\dh}n\'y Bj\"ork {\TH}orvaldsd\'ottir, Mathias M\"uller, Sarah Ebling
KwaiMind is a commercial image editing system that combines general editing capabilities with e-commerce specialization. It uses an agent-based data engine with 1.8 million editing pairs and a multimodal diffusion transformer trained through pre‑training, fine‑tuning, preference optimization, and online reinforcement learning. The system is guided by a vision‑language judge and specialized rewards for click‑through rate, text rendering, and product consistency, and it achieves top scores on ImgEdit, GEdit, REDEdit, and the new Ecom‑Bench, while improving predicted and actual CTR in offline and online experiments.
By Junlong Wu, Zijun Li, Yuting Hu, Jia Sun, Pengcheng Wei, Yimin Zhou, Honglie Wang, Huaiqing Wang, Dewen Fan, Fei Zuo, Haixuan Gao, Lihui Peng, Tingxuan She, Yuqing Li, Boheng Zhang, Fan Yang, Wenwu Ou
arXiv:2605.11151v3 Announce Type: replace
Abstract: Offline-to-online reinforcement learning (RL) improves sample efficiency by leveraging pre-collected datasets prior to online interaction. A key ch...
By Andrew Choi, Wei Xu
arXiv:2609.23997v1 Announce Type: cross
Abstract: Multi-robot collaboration could enable more efficient and scalable solutions to complex robotic tasks, but collaboration under partial observability...
By Dorian Benhamou Goldfajn, Mason Nakamura, Saaduddin Mahmud, Justin Svegliato, Kyle H. Wray, Shlomo Zilberstein
arXiv:2609.25864v1 Announce Type: cross
Abstract: Visual object removal can eliminate a target from video frames, yet its acoustic trace persists in the soundtrack, causing obvious audio-visual incon...
By Xinyue Guo, Jianxuan Yang, Daiguo Zhou, Jiagao Hu, Yuxuan Chen, Fei Wang, Jian Luan
Objective assessment of robotic surgery uses instrument kinematics, which must be reconstructed when only video is available. We introduce a kinematic reconstruction network for estimating instrument...
Sparse communication in decentralized zeroth-order learning requires compatible peer-state coordinates. We characterize this one-hop condition and develop \textsf{ZO-COSMO}, coupling two-query estimat...
Users commonly combine multiple Low-Rank Adaptation (LoRA) adapters to personalize images with different subjects, styles, and visual attributes. Yet inspecting adapters individually does not establis...
We present the first experiments on isolated sign language recognition (ISLR) for Icelandic Sign Language (ÍTM). We use ÍTM SignWiki, a dataset derived from a bilingual Icelandic--ÍTM online dictionar...