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Our Call for Papers for Berlin Buzzwords closes this Sunday, February 15!
We encourage everyone in modern data infrastructure, search and machine learning and focused on open source software projects to submit their talk proposals, especially first-timers and people from underrepresented groups! #bbuzz #OpenSource #Berlin #Conference #MachineLearning #Search #DataInfrastructure #DataScience

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[6/6]:
- Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning
Chi-Pin Huang, Yunze Man, Zhiding Yu, Min-Hung Chen, Jan Kautz, Yu-Chiang Frank Wang, Fu-En Yang
https://arxiv.org/abs/2601.09708 https://mastoxiv.page/@arXiv_csCV_bot/115898618760721320
- Universality of Many-body Projected Ensemble for Learning Quantum Data Distribution
Quoc Hoan Tran, Koki Chinzei, Yasuhiro Endo, Hirotaka Oshima
https://arxiv.org/abs/2601.18637 https://mastoxiv.page/@arXiv_quantph_bot/115967001797773134
- FROST: Filtering Reasoning Outliers with Attention for Efficient Reasoning
Haozheng Luo, Zhuolin Jiang, Md Zahid Hasan, Yan Chen, Soumalya Sarkar
https://arxiv.org/abs/2601.19001 https://mastoxiv.page/@arXiv_csCL_bot/115972068838908815
- Analysis of Shuffling Beyond Pure Local Differential Privacy
Shun Takagi, Seng Pei Liew
https://arxiv.org/abs/2601.19154 https://mastoxiv.page/@arXiv_csDS_bot/115971701218309765
- CryoLVM: Self-supervised Learning from Cryo-EM Density Maps with Large Vision Models
Weining Fu, Kai Shu, Kui Xu, Qiangfeng Cliff Zhang
https://arxiv.org/abs/2602.02620
- XtraLight-MedMamba for Classification of Neoplastic Tubular Adenomas
Sultana, Afsar, Rahu, Singh, Shula, Combs, Forchetti, Asari
https://arxiv.org/abs/2602.04819
- Flow-Based Conformal Predictive Distributions
Trevor Harris
https://arxiv.org/abs/2602.07633 https://mastoxiv.page/@arXiv_statML_bot/116045671088130364
- GOT-Edit: Geometry-Aware Generic Object Tracking via Online Model Editing
Shih-Fang Chen, Jun-Cheng Chen, I-Hong Jhuo, Yen-Yu Lin
https://arxiv.org/abs/2602.08550 https://mastoxiv.page/@arXiv_csCV_bot/116046486984991360
- UI-Venus-1.5 Technical Report
Venus Team, et al.
https://arxiv.org/abs/2602.09082 https://mastoxiv.page/@arXiv_csCV_bot/116050980295461008
- The Wisdom of Many Queries: Complexity-Diversity Principle for Dense Retriever Training
Xincan Feng, Noriki Nishida, Yusuke Sakai, Yuji Matsumoto
https://arxiv.org/abs/2602.09448 https://mastoxiv.page/@arXiv_csIR_bot/116051022881293649
- Intent Laundering: AI Safety Datasets Are Not What They Seem
Shahriar Golchin, Marc Wetter
https://arxiv.org/abs/2602.16729 https://mastoxiv.page/@arXiv_csCR_bot/116101884238965526
- The Metaphysics We Train: A Heideggerian Reading of Machine Learning
Heman Shakeri
https://arxiv.org/abs/2602.19028 https://mastoxiv.page/@arXiv_csCY_bot/116125225694943789
- Skill-Inject: Measuring Agent Vulnerability to Skill File Attacks
David Schmotz, Luca Beurer-Kellner, Sahar Abdelnabi, Maksym Andriushchenko
https://arxiv.org/abs/2602.20156 https://mastoxiv.page/@arXiv_csCR_bot/116125330557447048
- A Very Big Video Reasoning Suite
Maijunxian Wang, et al.
https://arxiv.org/abs/2602.20159 https://mastoxiv.page/@arXiv_csCV_bot/116125664801070747
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