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🐚 Scientists raise 300,000 surfclams offshore, proving open-ocean aquaculture can work
https://phys.org/news/2026-02-scientists-surfclams-offshore-ocean-aquaculture.html

Scientists raise 300,000 surfclams offshore, proving open-ocean aquaculture can work
Rutgers researchers have made a discovery that could change the future of seafood farming in New Jersey. A study led by marine scientist Daphne Munroe has shown that Atlantic surfclams can be successfully farmed in the open ocean. Her research, published in the North American Journal of Aquaculture, proves that offshore aquaculture is not only possible but promising. This method could help meet the increasing demand for seafood while protecting wild clam populations.

Faces who need new places: We picked 32 players who could use fresh starts with new teams https://www.espn.com/nfl/story/_/id/47955391/nfl-2026-offseason-draft-trade-free-agency-change-scenery

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/6]:
- Towards Scalable Oversight via Partitioned Human Supervision
Ren Yin, Takashi Ishida, Masashi Sugiyama
https://arxiv.org/abs/2510.22500 https://mastoxiv.page/@arXiv_csLG_bot/115451787490434401
- ContextPilot: Fast Long-Context Inference via Context Reuse
Yinsicheng Jiang, Yeqi Huang, Liang Cheng, Cheng Deng, Xuan Sun, Luo Mai
https://arxiv.org/abs/2511.03475 https://mastoxiv.page/@arXiv_csLG_bot/115502245581974540
- Metabolomic Biomarker Discovery for ADHD Diagnosis Using Interpretable Machine Learning
Nabil Belacel, Mohamed Rachid Boulassel
https://arxiv.org/abs/2601.11283 https://mastoxiv.page/@arXiv_csLG_bot/115921183182326799
- PhysE-Inv: A Physics-Encoded Inverse Modeling approach for Arctic Snow Depth Prediction
Akila Sampath, Vandana Janeja, Jianwu Wang
https://arxiv.org/abs/2601.17074
- SAGE-5GC: Security-Aware Guidelines for Evaluating Anomaly Detection in the 5G Core Network
Cristian Manca, Christian Scano, Giorgio Piras, Fabio Brau, Maura Pintor, Battista Biggio
https://arxiv.org/abs/2602.03596
- LORE: Jointly Learning the Intrinsic Dimensionality and Relative Similarity Structure From Ordina...
Anand, Helbling, Davenport, Berman, Alagapan, Rozell
https://arxiv.org/abs/2602.04192
- Towards Robust Scaling Laws for Optimizers
Alexandra Volkova, Mher Safaryan, Christoph H. Lampert, Dan Alistarh
https://arxiv.org/abs/2602.07712 https://mastoxiv.page/@arXiv_csLG_bot/116046369672796465
- Do We Need Adam? Surprisingly Strong and Sparse Reinforcement Learning with SGD in LLMs
Sagnik Mukherjee, Lifan Yuan, Pavan Jayasinha, Dilek Hakkani-T\"ur, Hao Peng
https://arxiv.org/abs/2602.07729 https://mastoxiv.page/@arXiv_csLG_bot/116046377539155485
- AceGRPO: Adaptive Curriculum Enhanced Group Relative Policy Optimization for Autonomous Machine L...
Yuzhu Cai, Zexi Liu, Xinyu Zhu, Cheng Wang, Siheng Chen
https://arxiv.org/abs/2602.07906 https://mastoxiv.page/@arXiv_csLG_bot/116046423413650658
- VESPO: Variational Sequence-Level Soft Policy Optimization for Stable Off-Policy LLM Training
Guobin Shen, Chenxiao Zhao, Xiang Cheng, Lei Huang, Xing Yu
https://arxiv.org/abs/2602.10693 https://mastoxiv.page/@arXiv_csLG_bot/116057229834947730
- KBVQ-MoE: KLT-guided SVD with Bias-Corrected Vector Quantization for MoE Large Language Models
Zukang Xu, Zhixiong Zhao, Xing Hu, Zhixuan Chen, Dawei Yang
https://arxiv.org/abs/2602.11184 https://mastoxiv.page/@arXiv_csLG_bot/116062537528208461
- MUSE: Multi-Tenant Model Serving With Seamless Model Updates
Correia, Ferreira, Martins, Bento, Guerreiro, Pereira, Gomes, Bono, Ferreira, Bizarro
https://arxiv.org/abs/2602.11776 https://mastoxiv.page/@arXiv_csLG_bot/116062952355379801
- Pawsterior: Variational Flow Matching for Structured Simulation-Based Inference
Jorge Carrasco-Pollo, Floor Eijkelboom, Jan-Willem van de Meent
https://arxiv.org/abs/2602.13813 https://mastoxiv.page/@arXiv_csLG_bot/116085828112928218
- Silent Inconsistency in Data-Parallel Full Fine-Tuning: Diagnosing Worker-Level Optimization Misa...
Hong Li, Zhen Zhou, Honggang Zhang, Yuping Luo, Xinyue Wang, Han Gong, Zhiyuan Liu
https://arxiv.org/abs/2602.14462 https://mastoxiv.page/@arXiv_csLG_bot/116085997857526328
- Divine Benevolence is an $x^2$: GLUs scale asymptotically faster than MLPs
Alejandro Francisco Queiruga
https://arxiv.org/abs/2602.14495 https://mastoxiv.page/@arXiv_csLG_bot/116086011618741857
- \"UberWeb: Insights from Multilingual Curation for a 20-Trillion-Token Dataset
DatologyAI, et al.
https://arxiv.org/abs/2602.15210 https://mastoxiv.page/@arXiv_csLG_bot/116090912256712568
- GLM-5: from Vibe Coding to Agentic Engineering
GLM-5-Team, et al.
https://arxiv.org/abs/2602.15763 https://mastoxiv.page/@arXiv_csLG_bot/116091080686771018
- Anatomy of Capability Emergence: Scale-Invariant Representation Collapse and Top-Down Reorganizat...
Jayadev Billa
https://arxiv.org/abs/2602.15997 https://mastoxiv.page/@arXiv_csLG_bot/116096541546306333
- AI-CARE: Carbon-Aware Reporting Evaluation Metric for AI Models
KC Santosh, Srikanth Baride, Rodrigue Rizk
https://arxiv.org/abs/2602.16042 https://mastoxiv.page/@arXiv_csLG_bot/116096581524696028
- Beyond Message Passing: A Symbolic Alternative for Expressive and Interpretable Graph Learning
Chuqin Geng, Li Zhang, Haolin Ye, Ziyu Zhao, Yuhe Jiang, Tara Saba, Xinyu Wang, Xujie Si
https://arxiv.org/abs/2602.16947 https://mastoxiv.page/@arXiv_csLG_bot/116102426238903124
toXiv_bot_toot

Crosslisted article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[1/2]:
- Bridge-RAG: An Abstract Bridge Tree Based Retrieval Augmented Generation Algorithm With Cuckoo Fi...
Li, Liu, Zong, Tao, Dai, Ren, Liu, Jiang, Yang
https://arxiv.org/abs/2603.26668 https://mastoxiv.page/@arXiv_csIR_bot/116322781593134028
- SRAG: RAG with Structured Data Improves Vector Retrieval
Shalin Shah, Srikanth Ryali, Ramasubbu Venkatesh
https://arxiv.org/abs/2603.26670 https://mastoxiv.page/@arXiv_csIR_bot/116322784870180864
- LITTA: Late-Interaction and Test-Time Alignment for Visually-Grounded Multimodal Retrieval
Seonok Kim
https://arxiv.org/abs/2603.26683 https://mastoxiv.page/@arXiv_csIR_bot/116322841916406330
- Agentic AI for Human Resources: LLM-Driven Candidate Assessment
Yuksel, Anees, Elneima, Hewavitharana, Al-Badrashiny, Sawaf
https://arxiv.org/abs/2603.26710 https://mastoxiv.page/@arXiv_csIR_bot/116322937601675587
- SEAR: Schema-Based Evaluation and Routing for LLM Gateways
Zecheng Zhang, Han Zheng, Yue Xu
https://arxiv.org/abs/2603.26728 https://mastoxiv.page/@arXiv_csDB_bot/116322627580095245
- SleepVLM: Explainable and Rule-Grounded Sleep Staging via a Vision-Language Model
Guifeng Deng, Pan Wang, Jiquan Wang, Shuying Rao, Junyi Xie, Wanjun Guo, Tao Li, Haiteng Jiang
https://arxiv.org/abs/2603.26738 https://mastoxiv.page/@arXiv_csCV_bot/116322739676378309
- Aesthetic Assessment of Chinese Handwritings Based on Vision Language Models
Chen Zheng, Yuxuan Lai, Haoyang Lu, Wentao Ma, Jitao Yang, Jian Wang
https://arxiv.org/abs/2603.26768 https://mastoxiv.page/@arXiv_csCV_bot/116323078149576728
- Learning to Select Visual In-Context Demonstrations
Eugene Lee, Yu-Chi Lin, Jiajie Diao
https://arxiv.org/abs/2603.26775 https://mastoxiv.page/@arXiv_csLG_bot/116322648878995047
- CRISP: Characterizing Relative Impact of Scholarly Publications
Hannah Collison, Benjamin Van Durme, Daniel Khashabi
https://arxiv.org/abs/2603.26791 https://mastoxiv.page/@arXiv_csDL_bot/116322621679820997
- GroupRAG: Cognitively Inspired Group-Aware Retrieval and Reasoning via Knowledge-Driven Problem S...
Xinyi Duan, Yuanrong Tang, Jiangtao Gong
https://arxiv.org/abs/2603.26807 https://mastoxiv.page/@arXiv_csIR_bot/116322959557860848
- In your own words: computationally identifying interpretable themes in free-text survey data
Jenny S Wang, Aliya Saperstein, Emma Pierson
https://arxiv.org/abs/2603.26930 https://mastoxiv.page/@arXiv_csCY_bot/116322780637316287
- Multilingual Stutter Event Detection for English, German, and Mandarin Speech
Felix Haas, Sebastian P. Bayerl
https://arxiv.org/abs/2603.26939 https://mastoxiv.page/@arXiv_csSD_bot/116322704289189130
- FormalProofBench: Can Models Write Graduate Level Math Proofs That Are Formally Verified?
Ravi, Ying, Nesterov, Krishnan, Uskuplu, Xia, Aswedige, Nashold
https://arxiv.org/abs/2603.26996 https://mastoxiv.page/@arXiv_csAI_bot/116322625941412681
- PHONOS: PHOnetic Neutralization for Online Streaming Applications
Waris Quamer, Mu-Ruei Tseng, Ghady Nasrallah, Ricardo Gutierrez-Osuna
https://arxiv.org/abs/2603.27001 https://mastoxiv.page/@arXiv_eessAS_bot/116322763598554193
- ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding
Jovana Kondic, et al.
https://arxiv.org/abs/2603.27064 https://mastoxiv.page/@arXiv_csCV_bot/116323214468792735
- daVinci-LLM:Towards the Science of Pretraining
Qin, Liu, Mi, Xie, Huang, Si, Lu, Feng, Wu, Liu, Luo, Hou, Guo, Qiao, Liu
https://arxiv.org/abs/2603.27164 https://mastoxiv.page/@arXiv_csAI_bot/116322653467105951
- LightMover: Generative Light Movement with Color and Intensity Controls
Zhou, Wang, Kim, Shu, Yu, Hold-Geoffroy, Chaturvedi, Wu, Lin, Cohen
https://arxiv.org/abs/2603.27209 https://mastoxiv.page/@arXiv_csCV_bot/116323263295656104
- Self-evolving AI agents for protein discovery and directed evolution
Tan, Zhang, Li, Yu, Zhong, Zhou, Dong, Hong
https://arxiv.org/abs/2603.27303 https://mastoxiv.page/@arXiv_csAI_bot/116322838641595927
- Inference-Time Structural Reasoning for Compositional Vision-Language Understanding
Amartya Bhattacharya
https://arxiv.org/abs/2603.27349 https://mastoxiv.page/@arXiv_csCV_bot/116323280006044500
- LLM Readiness Harness: Evaluation, Observability, and CI Gates for LLM/RAG Applications
Alexandre Cristov\~ao Maiorano
https://arxiv.org/abs/2603.27355 https://mastoxiv.page/@arXiv_csAI_bot/116322987708962414
- Heterogeneous Debate Engine: Identity-Grounded Cognitive Architecture for Resilient LLM-Based Eth...
Jakub Mas{\l}owski, Jaros{\l}aw A. Chudziak
https://arxiv.org/abs/2603.27404 https://mastoxiv.page/@arXiv_csAI_bot/116322999177460352
toXiv_bot_toot

Darth #Trump—who in the world can take this jerk seriously anymore? Who wants to do business with liars, contract breakers, criminals, and corrupt individuals, especially when it comes to matters of national security?
We shouldn’t pin our hopes on the midterm elections and wait around; instead, we should assume that things in the U.S. are only going to get worse. ❗

Raiders' jersey numbers for 2026 season https://www.raiders.com/news/raiders-jersey-numbers-for-2026-season-free-agency

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