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Vikings, RB Aaron Jones agree to revised contract to keep him in Minnesota for 2026 season https://www.nfl.com/news/vikings-rb-aaron-jones-agree-to-revised-contract-for-2026-season

Mumbai-based digital payments processor BillDesk agrees to acquire the Indian business of Worldline for an equity value of ~$70M, set to close in H2 2026 (The Economic Times)
https://economictimes.indiatimes.com/t

Billdesk to acquire Worldline’s India operations; deal values business at $70 million
Billdesk is set to acquire the India payments business of French payment giant Worldline for an estimated equity value of $70 million. In a press release Worldline said that it will be entering into a long-term technology and software pact with Billdesk, through which Worldline’s software stack will continue to remain operational in India. At an enterprise level the value of the deal was pegged at $43.6 million.

Neurotechnology and Cognitive Warfare #BCI

Neurotechnology and Cognitive Warfare
[Carl Emilio Lewis and Jonathan Kwik are researchers in international law at the TMC Asser Institute] The ‘application of neurotechnology raises [various] ethical, legal and societal issues and que…

Trump is 'not protecting Americans'
Senate minority leader, Chuck Schumer, said Democrats were right to remain seated when Trump called on the crowd to stand if they believed in protecting US citizens over undocumented immigrants,
a line that Republicans are now using to call out Democrats.
“Bottom line is very simple,
we agree we need to protect Americans.
He’s not,”
Schumer told CNN this morning.
“By his reckless ICE agency in Minnesota,

“Mike Johnson, House Republican extremists, and Donald Trump are why people missed their flights on Saturday.”
https://bsky.app/profile/chrisgeidner.bsky.social/post/3mi6bs2svuk26

Chris Geidner (@chrisgeidner.bsky.social)
This “lawmakers remain at a stalemate” framing is all over the place and is so bad. While technically accurate, it’s misleading and a disservice to readers. If Senate Rs, Senate Ds, & House Ds agree to something, but House Rs keep that deal from getting to Trump, the framing should reflect that.

All Substitution Is Local
Nidhish Shah, Shaurjya Mandal, Asfandyar Azhar
https://arxiv.org/abs/2604.01443 https://arxiv.org/pdf/2604.01443 https://arxiv.org/html/2604.01443
arXiv:2604.01443v1 Announce Type: new
Abstract: When does consulting one information source raise the value of another, and when does it diminish it? We study this question for Bayesian decision-makers facing finite actions. The interaction decomposes into two opposing forces: a complement force, measuring how one source moves beliefs to where the other becomes more useful, and a substitute force, measuring how much the current decision is resolved. Their balance obeys a localization principle: substitution requires an observation to cross a decision boundary, though crossing alone does not guarantee it. Whenever posteriors remain inside the current decision region, the substitute force vanishes, and sources are guaranteed to complement each other, even when one source cannot, on its own, change the decision. The results hold for arbitrarily correlated sources and are formalized in Lean 4. Substitution is confined to the thin boundaries where decisions change. Everywhere else, information cooperates. Code and proofs: https://github.com/nidhishs/all-substitution-is-local.
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Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[1/5]:
- Beyond In-Distribution Success: Scaling Curves of CoT Granularity for Language Model Generalization
Ru Wang, Wei Huang, Selena Song, Haoyu Zhang, Qian Niu, Yusuke Iwasawa, Yutaka Matsuo, Jiaxian Guo
https://arxiv.org/abs/2502.18273 https://mastoxiv.page/@arXiv_csCL_bot/114069031700102129
- Benchmarking NLP-supported Language Sample Analysis for Swiss Children's Speech
Anja Ryser, Yingqiang Gao, Sarah Ebling
https://arxiv.org/abs/2504.00780 https://mastoxiv.page/@arXiv_csCL_bot/114267149909002069
- Cultural Biases of Large Language Models and Humans in Historical Interpretation
Fabio Celli, Georgios Spathulas
https://arxiv.org/abs/2504.02572 https://mastoxiv.page/@arXiv_csCL_bot/114278467094094490
- BRIDGE: Benchmarking Large Language Models for Understanding Real-world Clinical Practice Text
Jiageng Wu, et al.
https://arxiv.org/abs/2504.19467 https://mastoxiv.page/@arXiv_csCL_bot/114420036189999973
- Understanding the Anchoring Effect of LLM with Synthetic Data: Existence, Mechanism, and Potentia...
Yiming Huang, Biquan Bie, Zuqiu Na, Weilin Ruan, Songxin Lei, Yutao Yue, Xinlei He
https://arxiv.org/abs/2505.15392 https://mastoxiv.page/@arXiv_csCL_bot/114550277171100272
- Just as Humans Need Vaccines, So Do Models: Model Immunization to Combat Falsehoods
Raza, Qureshi, Farooq, Lotif, Chadha, Pandya, Emmanouilidis
https://arxiv.org/abs/2505.17870 https://mastoxiv.page/@arXiv_csCL_bot/114572956853819813
- LingoLoop Attack: Trapping MLLMs via Linguistic Context and State Entrapment into Endless Loops
Fu, Jiang, Hong, Li, Guo, Yang, Chen, Zhang
https://arxiv.org/abs/2506.14493 https://mastoxiv.page/@arXiv_csCL_bot/114703502552989170
- GHTM: A Graph-based Hybrid Topic Modeling Approach with a Benchmark Dataset for the Low-Resource ...
Farhana Haque, Md. Abdur Rahman, Sumon Ahmed
https://arxiv.org/abs/2508.00605 https://mastoxiv.page/@arXiv_csCL_bot/114969875643478303
- Link Prediction for Event Logs in the Process Industry
Anastasia Zhukova, Thomas Walton, Christian E. Lobm\"uller, Bela Gipp
https://arxiv.org/abs/2508.09096 https://mastoxiv.page/@arXiv_csCL_bot/115020938764936882
- AirQA: A Comprehensive QA Dataset for AI Research with Instance-Level Evaluation
Huang, Cao, Zhang, Kang, Wang, Wang, Luo, Zheng, Qian, Chen, Yu
https://arxiv.org/abs/2509.16952 https://mastoxiv.page/@arXiv_csCL_bot/115253526588472475
- Multi-View Attention Multiple-Instance Learning Enhanced by LLM Reasoning for Cognitive Distortio...
Jun Seo Kim, Hyemi Kim, Woo Joo Oh, Hongjin Cho, Hochul Lee, Hye Hyeon Kim
https://arxiv.org/abs/2509.17292 https://mastoxiv.page/@arXiv_csCL_bot/115253586227941157
- Dual-Space Smoothness for Robust and Balanced LLM Unlearning
Han Yan, Zheyuan Liu, Meng Jiang
https://arxiv.org/abs/2509.23362 https://mastoxiv.page/@arXiv_csCL_bot/115293308293558024
- The Rise of AfricaNLP: Contributions, Contributors, Community Impact, and Bibliometric Analysis
Tadesse Destaw Belay, et al.
https://arxiv.org/abs/2509.25477 https://mastoxiv.page/@arXiv_csCL_bot/115298213432594791
- Open ASR Leaderboard: Towards Reproducible and Transparent Multilingual and Long-Form Speech Reco...
Srivastav, Zheng, Bezzam, Le Bihan, Koluguri, \.Zelasko, Majumdar, Moumen, Gandhi
https://arxiv.org/abs/2510.06961 https://mastoxiv.page/@arXiv_csCL_bot/115343748052193267
- Neuron-Level Analysis of Cultural Understanding in Large Language Models
Taisei Yamamoto, Ryoma Kumon, Danushka Bollegala, Hitomi Yanaka
https://arxiv.org/abs/2510.08284 https://mastoxiv.page/@arXiv_csCL_bot/115349533441895984
- CLMN: Concept based Language Models via Neural Symbolic Reasoning
Yibo Yang
https://arxiv.org/abs/2510.10063 https://mastoxiv.page/@arXiv_csCL_bot/115372392366793754
- Schema for In-Context Learning
Chen, Chen, Wang, Leong, Fung, Bernales, Aspuru-Guzik
https://arxiv.org/abs/2510.13905 https://mastoxiv.page/@arXiv_csCL_bot/115389057899856601
- Evaluating Latent Knowledge of Public Tabular Datasets in Large Language Models
Matteo Silvestri, Fabiano Veglianti, Flavio Giorgi, Fabrizio Silvestri, Gabriele Tolomei
https://arxiv.org/abs/2510.20351 https://mastoxiv.page/@arXiv_csCL_bot/115428615784704418
- LuxIT: A Luxembourgish Instruction Tuning Dataset from Monolingual Seed Data
Julian Valline, Cedric Lothritz, Siwen Guo, Jordi Cabot
https://arxiv.org/abs/2510.24434 https://mastoxiv.page/@arXiv_csCL_bot/115457025096322944
- Surfacing Subtle Stereotypes: A Multilingual, Debate-Oriented Evaluation of Modern LLMs
Muhammed Saeed, Muhammad Abdul-mageed, Shady Shehata
https://arxiv.org/abs/2511.01187 https://mastoxiv.page/@arXiv_csCL_bot/115491321130591723
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