Tootfinder

Last leg on our brief history of NLP (so far) is the advent of large language models with GPT-3 in 2020 and the introduction of learning from the prompt (aka few-shot learning).
T. B. Brown et al. (2020). Language models are few-shot learners. NIPS'20
https://…

TopicAttack: An Indirect Prompt Injection Attack via Topic Transition
Yulin Chen, Haoran Li, Yuexin Li, Yue Liu, Yangqiu Song, Bryan Hooi
https://arxiv.org/abs/2507.13686

TopicAttack: An Indirect Prompt Injection Attack via Topic Transition
Large language models (LLMs) have shown remarkable performance across a range of NLP tasks. However, their strong instruction-following capabilities and inability to distinguish instructions from data content make them vulnerable to indirect prompt injection attacks. In such attacks, instructions with malicious purposes are injected into external data sources, such as web documents. When LLMs retrieve this injected data through tools, such as a search engine and execute the injected instruction…

Precision spectral measurements of Chromium and Titanium from 10 to 250 GeV$/n$ and sub-Iron to Iron ratio with the Calorimetric Electron Telescope on the ISS
O. Adriani, Y. Akaike, K. Asano, Y. Asaoka, E. Berti, P. Betti, G. Bigongiari, W. R. Binns, M. Bongi, P. Brogi, A. Bruno, N. Cannady, G. Castellini, C. Checchia, M. L. Cherry, G. Collazuol, G. A. de Nolfo, K. Ebisawa, A. W. Ficklin, H. Fuke, S. Gonzi, T. G. Guzik, T. Hams, K. Hibino, M. Ichimura, M. H. Israel, K. Kasahara, J. Kat…

Precision spectral measurements of Chromium and Titanium from 10 to 250 GeV$/n$ and sub-Iron to Iron ratio with the Calorimetric Electron Telescope on the ISS
The Calorimetric Electron Telescope (CALET), in operation on the International Space Station since 2015, collected a large sample of cosmic-ray (CR) iron and sub-iron events over a wide energy interval. In this paper we report an update of our previous measurement of the iron flux and we present - for the first time - a high statistics measurement of the spectra of two sub-iron elements Cr and Ti in the energy interval from 10 to 250 GeV/n. The analyses are based on 8 years of data. Differently…

CSBrain: A Cross-scale Spatiotemporal Brain Foundation Model for EEG Decoding
Yuchen Zhou, Jiamin Wu, Zichen Ren, Zhouheng Yao, Weiheng Lu, Kunyu Peng, Qihao Zheng, Chunfeng Song, Wanli Ouyang, Chao Gou
https://arxiv.org/abs/2506.23075

CSBrain: A Cross-scale Spatiotemporal Brain Foundation Model for EEG Decoding
Understanding and decoding brain activity from electroencephalography (EEG) signals is a fundamental challenge in neuroscience and AI, with applications in cognition, emotion recognition, diagnosis, and brain-computer interfaces. While recent EEG foundation models advance generalized decoding via unified architectures and large-scale pretraining, they adopt a scale-agnostic dense modeling paradigm inherited from NLP and vision. This design neglects a core property of neural activity: cross-scal…