Following the fatal shootings of American citizens Renee Good and Alex Pretti by federal agents in Minneapolis last month,
Democrats have refused to support long-term funding for the Department of Homland Security unless Republicans agree to reforms on the tactics of federal agents carrying out Donald Trump’s immigration crackdown.
“The American people rightfully expect their elected representatives to take action to rein in ICE and ensure no more lives are lost,” Senate minorit…
I agree with SF Chronicle columnist Allison Arieff that we should follow in Paris' footsteps by electing socialist mayors. Ok, she doesn't mention what party they belong to, but Allison does praise Anne Hidalgo and Emmanuel Grégoire.
https://www.sfchronicle.com/opini…
Filing: Samsung plans to acquire $1.73B of its stock for employee and executive compensation, as part of a performance-linked scheme introduced in October 2025 (Kyu-seok Shim/Reuters)
https://www.reuters.com/business/samsung-e…
ENGIE has acquired UK Power Networks. Does this mean that the UK’s energy infrastructure is now more integrated with the EU than it was before Brexit?
https://en.newsroom.engie.com/news/eng
Simulation and optimization of the Active Magnetic Shield of the n2EDM experiment
N. J. Ayres, G. Ban, G. Bison, K. Bodek, V. Bondar, T. Bouillaud, G. L. Caratsch, E. Chanel, W. Chen, C. Crawford, V. Czamler, C. B. Doorenbos, S. Emmeneger, S. K. Ermakov, M. Ferry, M. Fertl, A. Fratangelo, D. Galbinski, W. C. Griffith, Z. D. Grujic, K. Kirch, V. Kletzl, J. Krempel, B. Lauss, T. Lefort, A. Lejuez, K. Michielsen, J. Micko, P. Mullan, O. Naviliat-Cuncic, F. M. Piegsa, G. Pignol, C. Pistillo, I. Rien\"acker, D. Ries, S. Roccia, D. Rozp\k{e}dzik, L. Sanchez-Real Zielniewicz, N. von Schickh, P. Schmidt-Wellenburg, E. P. Segarra, L. Segner, N. Severijns, K. Svirina, J. Thorne, J. Vankeirsbilck, N. Yazdandoost, J. Zejma, N. Ziehl, G. Zsigmond
https://arxiv.org/abs/2601.22960 https://arxiv.org/pdf/2601.22960 https://arxiv.org/html/2601.22960
arXiv:2601.22960v1 Announce Type: new
Abstract: The n2EDM experiment at the Paul Scherrer Institute aims to conduct a high-sensitivity search for the electric dipole moment of the neutron. Magnetic stability and control are achieved through a combination of passive shielding, provided by a magnetically shielded room (MSR), and a surrounding active field compensation system by an Active Magnetic Shield (AMS). The AMS is a feedback-controlled system of eight coils spanned on an irregular grid, designed to provide magnetic stability to the enclosed volume by actively suppressing external magnetic disturbances. It can compensate static and variable magnetic fields up to $\pm 50$ $\mu$T (homogeneous components) and $\pm 5$ $\mu$T/m (first-order gradients), suppressing them to a few $\mu$T in the sub-Hertz frequency range. We present a full finite element simulation of magnetic fields generated by the AMS in the presence of the MSR. This simulation is of sufficient accuracy to approach our measurements. We demonstrate how the simulation can be used with an example, obtaining an optimal number and placement of feedback sensors using genetic algorithms.
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Über die Hälfte der bislang eingereichten nationalen #Klimapläne (NDCs) enthalten inzwischen konkrete Ziele zur #Elektromobilität.
66 Länder, darunter viele aus dem globalen Süden, haben erstmals entsprechende Vorgaben aufgenommen. Diese Staaten stehen heute für mehr als …
🪨 Diversifying lithium-rich mineral sources with petalite
#lithium
Collective Electronic Polarization Drives Charge Asymmetry at Oil-Water Interfaces
Gabriele Amante, Klaudia Mrazikova, Gabriele Centi, Sylvie Roke, Ali Hassanali, Giuseppe Cassone
https://arxiv.org/abs/2603.24142 https://arxiv.org/pdf/2603.24142 https://arxiv.org/html/2603.24142
arXiv:2603.24142v1 Announce Type: new
Abstract: Why kinetically stable oil droplets in water spontaneously acquire a negative charge remains one of the most vigorously debated questions in interfacial science. Here, we combine neural-network based deep potential molecular dynamics with a data-driven and information theory approach to probe the real-space electron density at an extended decane-water interface. While decane-water clusters show nearly symmetric forward and backward charge transfer (CT) and thus negligible net CT, the extended interface displays a systematic electronic asymmetry, yielding a net CT from water to the hydrocarbon phase producing an average surface charge density of $\sim0.006~e^{-}\,\mathrm{nm}^{-2}$ on the oil phase. This imbalance is accompanied by much larger intra-phase self-polarization, particularly within the hydrocarbon phase, demonstrating that collective many-body polarization dominates the interfacial electronic response. Structural analysis reveals an asymmetry between forward C--H$\cdots$O and backward O--H$\cdots$C motifs, providing a microscopic origin for a net CT from one phase to the other. Curiously, both the water O--H and decane C--H covalent bonds incur subtle contractions which originate from a response to the charge-separation layers at the interface. These features are fully consistent with the weak improper hydrogen-bonds forming at the oil-water interface that results in blue-shifts of the C-H modes.
toXiv_bot_toot
Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[2/5]:
- POTSA: A Cross-Lingual Speech Alignment Framework for Speech-to-Text Translation
Li, Cui, Wang, Ge, Huang, Li, Peng, Lu, Tashi, Wang, Dang
https://arxiv.org/abs/2511.09232 https://mastoxiv.page/@arXiv_csCL_bot/115541846907664054
- Beyond Elicitation: Provision-based Prompt Optimization for Knowledge-Intensive Tasks
Yunzhe Xu, Zhuosheng Zhang, Zhe Liu
https://arxiv.org/abs/2511.10465 https://mastoxiv.page/@arXiv_csCL_bot/115547607561282911
- $\pi$-Attention: Periodic Sparse Transformers for Efficient Long-Context Modeling
Dong Liu, Yanxuan Yu
https://arxiv.org/abs/2511.10696 https://mastoxiv.page/@arXiv_csCL_bot/115564418836654965
- Based on Data Balancing and Model Improvement for Multi-Label Sentiment Classification Performanc...
Zijin Su, Huanzhu Lyu, Yuren Niu, Yiming Liu
https://arxiv.org/abs/2511.14073 https://mastoxiv.page/@arXiv_csCL_bot/115575715073023141
- HEAD-QA v2: Expanding a Healthcare Benchmark for Reasoning
Alexis Correa-Guill\'en, Carlos G\'omez-Rodr\'iguez, David Vilares
https://arxiv.org/abs/2511.15355 https://mastoxiv.page/@arXiv_csCL_bot/115581410328165116
- Towards Hyper-Efficient RAG Systems in VecDBs: Distributed Parallel Multi-Resolution Vector Search
Dong Liu, Yanxuan Yu
https://arxiv.org/abs/2511.16681 https://mastoxiv.page/@arXiv_csCL_bot/115603508442305146
- Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Transla...
Marii Ojastu, Hele-Andra Kuulmets, Aleksei Dorkin, Marika Borovikova, Dage S\"arg, Kairit Sirts
https://arxiv.org/abs/2511.17290 https://mastoxiv.page/@arXiv_csCL_bot/115604083224487885
- A Systematic Study of In-the-Wild Model Merging for Large Language Models
O\u{g}uz Ka\u{g}an Hitit, Leander Girrbach, Zeynep Akata
https://arxiv.org/abs/2511.21437 https://mastoxiv.page/@arXiv_csCL_bot/115621178703846052
- CREST: Universal Safety Guardrails Through Cluster-Guided Cross-Lingual Transfer
Lavish Bansal, Naman Mishra
https://arxiv.org/abs/2512.02711 https://mastoxiv.page/@arXiv_csCL_bot/115655090475535157
- Multilingual Medical Reasoning for Question Answering with Large Language Models
Pietro Ferrazzi, Aitor Soroa, Rodrigo Agerri
https://arxiv.org/abs/2512.05658 https://mastoxiv.page/@arXiv_csCL_bot/115683267711014189
- OnCoCo 1.0: A Public Dataset for Fine-Grained Message Classification in Online Counseling Convers...
Albrecht, Lehmann, Poltermann, Rudolph, Steigerwald, Stieler
https://arxiv.org/abs/2512.09804 https://mastoxiv.page/@arXiv_csCL_bot/115700409397020978
- Does Tone Change the Answer? Evaluating Prompt Politeness Effects on Modern LLMs: GPT, Gemini, an...
Hanyu Cai, Binqi Shen, Lier Jin, Lan Hu, Xiaojing Fan
https://arxiv.org/abs/2512.12812 https://mastoxiv.page/@arXiv_csCL_bot/115729149622659403
- Beg to Differ: Understanding Reasoning-Answer Misalignment Across Languages
Ovalle, Ross, Ruder, Williams, Ullrich, Ibrahim, Sagun
https://arxiv.org/abs/2512.22712 https://mastoxiv.page/@arXiv_csCL_bot/115808161882146194
- Activation Steering for Masked Diffusion Language Models
Adi Shnaidman, Erin Feiglin, Osher Yaari, Efrat Mentel, Amit Levi, Raz Lapid
https://arxiv.org/abs/2512.24143 https://mastoxiv.page/@arXiv_csCL_bot/115819533211103315
- JMedEthicBench: A Multi-Turn Conversational Benchmark for Evaluating Medical Safety in Japanese L...
Liu, Li, Niu, Zhang, Xun, Hou, Wang, Iwasawa, Matsuo, Hatakeyama-Sato
https://arxiv.org/abs/2601.01627 https://mastoxiv.page/@arXiv_csCL_bot/115847901607405421
- FACTUM: Mechanistic Detection of Citation Hallucination in Long-Form RAG
Dassen, Kotula, Murray, Yates, Lawrie, Kayi, Mayfield, Duh
https://arxiv.org/abs/2601.05866 https://mastoxiv.page/@arXiv_csCL_bot/115881545684182376
- {\dag}DAGGER: Distractor-Aware Graph Generation for Executable Reasoning in Math Problems
Zabir Al Nazi, Shubhashis Roy Dipta, Sudipta Kar
https://arxiv.org/abs/2601.06853 https://mastoxiv.page/@arXiv_csCL_bot/115887753245730019
- Symphonym: Universal Phonetic Embeddings for Cross-Script Name Matching
Stephen Gadd
https://arxiv.org/abs/2601.06932 https://mastoxiv.page/@arXiv_csCL_bot/115887767008671765
- LLMs versus the Halting Problem: Revisiting Program Termination Prediction
Sultan, Armengol-Estape, Kesseli, Vanegue, Shahaf, Adi, O'Hearn
https://arxiv.org/abs/2601.18987 https://mastoxiv.page/@arXiv_csCL_bot/115972010510378715
- MuVaC: A Variational Causal Framework for Multimodal Sarcasm Understanding in Dialogues
Diandian Guo, Fangfang Yuan, Cong Cao, Xixun Lin, Chuan Zhou, Hao Peng, Yanan Cao, Yanbing Liu
https://arxiv.org/abs/2601.20451 https://mastoxiv.page/@arXiv_csCL_bot/115977891530875024
toXiv_bot_toot
Sequential Counterfactual Inference for Temporal Clinical Data: Addressing the Time Traveler Dilemma
Jingya Cheng, Alaleh Azhir, Jiazi Tian, Hossein Estiri
https://arxiv.org/abs/2602.21168 https://arxiv.org/pdf/2602.21168 https://arxiv.org/html/2602.21168
arXiv:2602.21168v1 Announce Type: new
Abstract: Counterfactual inference enables clinicians to ask "what if" questions about patient outcomes, but standard methods assume feature independence and simultaneous modifiability -- assumptions violated by longitudinal clinical data. We introduce the Sequential Counterfactual Framework, which respects temporal dependencies in electronic health records by distinguishing immutable features (chronic diagnoses) from controllable features (lab values) and modeling how interventions propagate through time. Applied to 2,723 COVID-19 patients (383 Long COVID heart failure cases, 2,340 matched controls), we demonstrate that 38-67% of patients with chronic conditions would require biologically impossible counterfactuals under naive methods. We identify a cardiorenal cascade (CKD -> AKI -> HF) with relative risks of 2.27 and 1.19 at each step, illustrating temporal propagation that sequential -- but not naive -- counterfactuals can capture. Our framework transforms counterfactual explanation from "what if this feature were different?" to "what if we had intervened earlier, and how would that propagate forward?" -- yielding clinically actionable insights grounded in biological plausibility.
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