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Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders多模态变分自编码器中相依专家分布的聚合

Rogelio A. Mancisidor, Robert Jenssen, Shujian Yu, Michael Kampffmeyer

Lightweight Protocols for Distributed Private Quantile Estimation分布式隐私分位数估计的轻量级协议

Anders Aamand, Fabrizio Boninsegna, Abigail Gentle, Jacob Imola, Rasmus Pagh

Breaking the $n^1.5$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition通过隐私扩展图分解突破隐私高效图稀疏化的 $n^{1.5}$ 加性误差壁垒

Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrović, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu

Improved Approximations for Hard Graph Problems using Predictions利用预测改进困难图问题的近似算法

Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu

Graph Neural Network Generalization With Gaussian Mixture Model Based Augmentation基于高斯混合模型增强的图神经网络泛化

Yassine Abbahaddou, Fragkiskos D. Malliaros, Johannes F. Lutzeyer, Amine M. Aboussalah, Michalis Vazirgiannis

LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language ModelsLMRL Gym：语言模型多轮强化学习基准

Marwa Abdulhai, Isadora White, Charlie Victor Snell, Charles Sun, Joey Hong, Yuexiang Zhai, Kelvin Xu, Sergey Levine

Task Generalization with Autoregressive Compositional Structure: Can Learning from $D$ Tasks Generalize to $D^T$ Tasks?基于自回归组合结构的任务泛化：从 $D$ 个任务学习能否泛化至 $D^T$ 个任务？

Amirhesam Abedsoltan, Huaqing Zhang, Kaiyue Wen, Hongzhou Lin, Jingzhao Zhang, Mikhail Belkin

Consensus Is All You Get: The Role of Attention in Transformers你所能得到的只有共识：注意力在 Transformer 中的作用

Álvaro Rodrı́guez Abella, João Pedro Silvestre, Paulo Tabuada

Soup-of-Experts: Pretraining Specialist Models via Parameters AveragingSoup-of-Experts：通过参数平均预训练专家模型

Pierre Ablin, Angelos Katharopoulos, Skyler Seto, David Grangier

Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models参数量与浮点运算量：混合专家语言模型最优稀疏度的缩放定律

Samira Abnar, Harshay Shah, Dan Busbridge, Alaaeldin El-Nouby, Joshua M. Susskind, Vimal Thilak

Grokking in the Wild: Data Augmentation for Real-World Multi-Hop Reasoning with Transformers真实环境中的顿悟学习：面向 Transformer 现实多跳推理的数据增强

Roman Abramov, Felix Steinbauer, Gjergji Kasneci

EnIGMA: Interactive Tools Substantially Assist LM Agents in Finding Security VulnerabilitiesEnIGMA：交互式工具显著帮助语言模型智能体发现安全漏洞

Talor Abramovich, Meet Udeshi, Minghao Shao, Kilian Lieret, Haoran Xi, Kimberly Milner, Sofija Jancheska, John Yang, Carlos E Jimenez, Farshad Khorrami, Prashanth Krishnamurthy, Brendan Dolan-Gavitt, Muhammad Shafique, Karthik R Narasimhan, Ramesh Karri, Ofir Press

Star Attention: Efficient LLM Inference over Long Sequences星形注意力：面向长序列的高效大语言模型推理

Shantanu Acharya, Fei Jia, Boris Ginsburg

Geometric Median (GM) Matching for Robust k-Subset Selection from Noisy Data用于从噪声数据中稳健选择 k 元子集的几何中位数匹配

Anish Acharya, Sujay Sanghavi, Alex Dimakis, Inderjit S Dhillon

Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo基于序贯蒙特卡洛的潜在空间逆问题采样

Idan Achituve, Hai Victor Habi, Amir Rosenfeld, Arnon Netzer, Idit Diamant, Ethan Fetaya

An in depth look at the Procrustes-Wasserstein distance: properties and barycenters深入解析 Procrustes–Wasserstein 距离：性质与重心

Davide Adamo, Marco Corneli, Manon Vuillien, Emmanuelle Vila

From Mechanistic Interpretability to Mechanistic Biology: Training, Evaluating, and Interpreting Sparse Autoencoders on Protein Language Models从机制可解释性到机制生物学：蛋白质语言模型稀疏自编码器的训练、评估与解释

Etowah Adams, Liam Bai, Minji Lee, Yiyang Yu, Mohammed Alquraishi

单位Department of Systems Biology, Columbia University · Ginkgo Bioworks, Boston · Ginkgo BioworksOpenAlex 论文记录 ↗

Sparse Training from Random Initialization: Aligning Lottery Ticket Masks using Weight Symmetry从随机初始化开始的稀疏训练：利用权重对称性对齐彩票掩码

Mohammed Adnan, Rohan Jain, Ekansh Sharma, Rahul Krishnan, Yani Ioannou

Design Considerations in Offline Preference-based RL离线偏好强化学习中的设计考量

Alekh Agarwal, Christoph Dann, Teodor Vanislavov Marinov

Optimal Fair Learning Robust to Adversarial Distribution Shift对对抗性分布偏移稳健的最优公平学习

Sushant Agarwal, Amit Deshpande, Rajmohan Rajaraman, Ravi Sundaram

FedECADO: A Dynamical System Model of Federated LearningFedECADO：联邦学习的动力系统模型

Aayushya Agarwal, Gauri Joshi, Lawrence Pileggi

The Missing Alignment Link of In-context Learning on Sequences序列上下文学习中缺失的对齐环节

Harshvardhan Agarwal, Sunita Sarawagi

Proto Successor Measure: Representing the Behavior Space of an RL Agent原型后继测度：表征强化学习智能体的行为空间

Siddhant Agarwal, Harshit Sikchi, Peter Stone, Amy Zhang

AlphaVerus: Bootstrapping Formally Verified Code Generation through Self-Improving Translation and TreefinementAlphaVerus：通过自改进翻译与 Treefinement 自举生成形式化验证代码

Pranjal Aggarwal, Bryan Parno, Sean Welleck

NextCoder: Robust Adaptation of Code LMs to Diverse Code EditsNextCoder：代码语言模型对多样化代码编辑的稳健适应

Tushar Aggarwal, Swayam Singh, Abhijeet Awasthi, Aditya Kanade, Nagarajan Natarajan

FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearchFunBO：利用 FunSearch 发现贝叶斯优化的采集函数

Virginia Aglietti, Ira Ktena, Jessica Schrouff, Eleni Sgouritsa, Francisco Ruiz, Alan Malek, Alexis Bellot, Silvia Chiappa

Understanding the difficulties of posterior predictive estimation理解后验预测估计的难点

Abhinav Agrawal, Justin Domke

Optimal Sensor Scheduling and Selection for Continuous-Discrete Kalman Filtering with Auxiliary Dynamics具有辅助动力学的连续—离散卡尔曼滤波最优传感器调度与选择

Mohamad Al Ahdab, John Leth, Zheng-Hua Tan

Online Laplacian-Based Representation Learning in Reinforcement Learning强化学习中的在线拉普拉斯表征学习

Maheed H. Ahmed, Jayanth Bhargav, Mahsa Ghasemi

Otter: Generating Tests from Issues to Validate SWE PatchesOtter：从问题单生成测试以验证软件工程补丁

Toufique Ahmed, Jatin Ganhotra, Rangeet Pan, Avraham Shinnar, Saurabh Sinha, Martin Hirzel