3DLLM-Mem: Long-Term Spatial-Temporal Memory for Embodied 3D Large Language Model
Wenbo Hu, Yining Hong, Yanjun Wang, Leison Gao, Zibu Wei, Xingcheng Yao, Nanyun Peng, Yonatan Bitton, Idan Szpektor, Kai-Wei Chang
3D-Prover: Diversity Driven Theorem Proving With Determinantal Point Processes
Sean Lamont, Christian Walder, Amir Dezfouli, Paul Montague, Michael Norrish
A Unified Approach to Submodular Maximization Under Noise
Kshipra Bhawalkar, Yang Cai, Zhe Feng, Christopher Liaw, Tao Lin*
Additive Models Explained: A Computational Complexity Approach
Shahaf Bassan, Michal Moshkovitz, Guy Katz
AI Debate Aids Assessment of Controversial Claims
Salman Rahman, Sheriff Issaka, Ashima Suvarna, Genglin Liu, James Shiffer, Jaeyoung Lee, Md Rizwan Parvez, Hamid Palangi, Shi Feng, Nanyun Peng, Yejin Choi, Julian Michael, Liwei Jiang, Saadia Gabriel
AI-Generated Video Detection via Perceptual Straightening
Christian Internò, Robert Geirhos, Markus Olhofer, Sunny Liu, Barbara Hammer, David Klindt
Analyzing Similarity Metrics for Data Selection for Language Model Pretraining
Dylan Sam*, Ayan Chakrabarti, Afshin Rostamizadeh, Srikumar Ramalingam, Gui Citovsky, Sanjiv Kumar
An Ellipsoid Algorithm for Online Convex Optimization
Zakaria Mhammedi
Beyond Least Squares: Uniform Approximation and the Hidden Cost of Misspecification
Davide Maran, Csaba Szepesvári
BioReason: Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model
Adibvafa Fallahpour, Andrew Magnuson, Purav Gupta, Shihao Ma, Jack Naimer, Arnav Shah, Haonan Duan, Omar Ibrahim, Hani Goodarzi, Chris J. Maddison, Bo Wang
Bridging Sign and Spoken Languages: Pseudo Gloss Generation for Sign Language Translation
Jianyuan Guo*, Peike Li, Trevor Cohn
Closed-Form Training Dynamics Reveal Learned Features and Linear Structure in Word2Vec-Like Models
Dhruva Karkada, James B. Simon, Yasaman Bahri, Michael R. DeWeese
Consistently Simulating Human Personas with Multi-Turn Reinforcement Learning
Marwa Abdulhai, Ryan Cheng, Donovan Clay, Tim Althoff, Sergey Levine, Natasha Jaques
Constructing an Optimal Behavior Basis for the Option Keyboard
Lucas N. Alegre, Ana L. C. Bazzan, André Barreto, Bruno C. da Silva
Contextual Dynamic Pricing with Heterogeneous Buyers
Thodoris Lykouris, Sloan Nietert, Princewill Okoroafor, Chara Podimata, Julian Zimmert
Data-Adaptive Exposure Thresholds Under Network Interference
Vydhourie Thiyageswaran, Tyler H. McCormick, Jennifer Brennan
DataRater: Meta-Learned Dataset Curation
Dan A. Calian, Gregory Farquhar, Iurii Kemaev, Luisa M. Zintgraf, Matteo Hessel, Jeremy Shar, Junhyuk Oh, András György, Tom Schaul, Jeffrey Dean, Hado van Hasselt, David Silver
Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates
Andrew Lowy, Daogao Liu
Dimension-free Score Matching and Time Bootstrapping for Diffusion Models
Syamantak Kumar*, Dheeraj Nagaraj, Purnamrita Sarkar
EA3D: Online Open-World 3D Object Extraction from Streaming Videos
Xiaoyu Zhou, Jingqi Wang, Yuang Jia, Yongtao Wang, Deqing Sun, Ming-Hsuan Yang
Efficient Adaptive Federated Optimization
Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer, Tian Li
Efficient Data Selection at Scale via Influence Distillation
Mahdi Nikdan*, Vincent Cohen-Addad, Dan Alistarh, Vahab Mirrokni
Efficient Spectral Control of Partially Observed Linear Dynamical Systems
Anand Brahmbhatt, Gon Buzaglo, Sofiia Druchyna, Elad Hazan
Efficiently Verifiable Proofs of Data Attribution
Ari Karchmer, Martin Pawelcyzk, Seth Neel
Emergent Temporal Correspondences from Video Diffusion Transformers
Jisu Nam, Soowon Son, Dahyun Chung, Jiyoung Kim, Siyoon Jin, Junhwa Hur, Seungryong Kim
Enhancing Personalized Multi-Turn Dialogue with\nCuriosity Reward
Yanming Wan*, Jiaxing Wu, Marwa Abdulhai, Lior Shani, Natasha Jaques
Escaping Collapse: The Strength of Weak Data for Large Language Model Training
Kareem Amin, Sara Babakniya, Alex Bie, Weiwei Kong, Umar Syed, Sergei Vassilvitskii
EUGens: Efficient, Unified, and General Dense Layers
Sang Min Kim, Byeongchan Kim, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Rahul Kidambi, Dongseok Shim, Avinava Dubey, Snigdha Chaturvedi, Min-hwan Oh, Krzysztof Choromanski
Exact and Linear Convergence for Federated Learning Under Arbitrary Client Participation Is Attainable
Bicheng Ying, Zhe Li, HaiboYag
Exploring Diffusion Transformer Designs via Grafting
Keshigeyan Chandrasegaran, Michael Poli, Daniel Y. Fu, Dongjun Kim, Lea M. Hadzic, Manling Li, Agrim Gupta, Stefano Massaroli, Azalia Mirhoseini, Juan Carlos Niebles, Stefano Ermon, Li Fei-Fei
Exploring the Limits of Strong Membership Inference Attacks on Large Language Models
Jamie Hayes, Ilia Shumailov, Christopher A. Choquette-Choo, Matthew Jagielski, Georgios Kaissis, Milad Nasr, Meenatchi Sundaram Muthu Selva Annamalai, Niloofar Mireshghallah, Igor Shilov, Matthieu Meeus, Yves-Alexandre de Montjoye, Katherine Lee, Franziska Boenisch, Adam Dziedzic, A. Feder Cooper
Fast Attention Mechanisms: A Tale of Parallelism
Jingwen Liu, Hantao Yu, Clayton Sanford, Alexandr Andoni, Daniel Hsu
Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime
Amit Attia, Matan Schliserman, Uri Sherman, Tomer Koren
Fine-Grained Preference Optimization Improves Spatial Reasoning in VLMs
Yifan Shen, Yuanzhe Liu, Jingyuan Zhu, Xu Cao, Xiaofeng Zhang, Yixiao He, Wenming Ye, James M. Rehg, Ismini Lourentzou
Force Prompting: Video Generation Models Can Learn and Generalize Physics-based Control Signals
Nate Gillman, Charles Herrmann, Michael Freeman, Daksh Aggarwal, Evan Luo, Deqing Sun, Chen Sun
From Contextual Combinatorial Semi-Bandits to Bandit List Classification: Improved Sample Complexity with Sparse Rewards
Liad Erez, Tomer Koren
From Dormant to Deleted: Tamper-Resistant Unlearning Through Weight-Space Regularization
Shoaib Ahmed Siddiqui, Adrian Weller, David Krueger, Gintare Karolina Dziugaite, Michael C. Mozer, Eleni Triantafillou
From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning
Eric Zhao, Pranjal Awasthi, Nika Haghtalab
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation
Sohyun Lee, Yeho Gwon, Lukas Hoyer, Suha Kwak
Gatekeeper: Improving Model Cascades Through Confidence Tuning
Stephan Rabanser*, Nathalie Rauschmayr, Achin Kulshrestha, Petra Poklukar, Wittawat Jitkrittum, Sean Augenstein, Congchao Wang, Federico Tombari
Generating Creative Chess Puzzles
Xidong Feng, Vivek Veeriah, Marcus Chiam, Michael Dennis, Ryan Pachauri, Thomas Tumiel, Federico Barbero*, Johan Obando-Ceron*, Jiaxin Shi, Satinder Singh, Shaobo Hou, Nenad Tomašev, Tom Zahavy
GIST: Greedy Independent Set Thresholding for Max-Min Diversification with Submodular Utility
Matthew Fahrbach, Srikumar Ramalingam, Morteza Zadimoghaddam, Sara Ahmadian, Gui Citovsky, Giulia DeSalvo
Heterogeneous Swarms: Jointly Optimizing Model Roles and Weights for Multi-LLM Systems
Shangbin Feng*, Zifeng Wang, Palash Goyal, Yike Wang, Weijia Shi, Huang Xia, Hamid Palangi, Luke Zettlemoyer, Yulia Tsvetkov, Chen-Yu Lee, Tomas Pfister
Hierarchical Retrieval: The Geometry and a Pretrain-Finetune Recipe
Chong You, Rajesh Jayaram, Ananda Theertha Suresh, Robin Nittka, Felix Yu, Sanjiv Kumar
High-Dimensional Calibration from Swap Regret
Maxwell Fishelson, Noah Golowich, Mehryar Mohri, Jon Schneider
HoliGS: Holistic Gaussian Splatting for Embodied View Synthesis
Xiaoyuan Wang, Yizhou Zhao, Botao Ye, Xiaojun Shan, Weijie Lyu, Lu Qi, Kelvin C.K. Chan, Yinxiao Li, Ming-Hsuan Yang
Hybrid Latent Reasoning via Reinforcement Learning
Zhenrui Yue, Bowen Jin, Huimin Zeng, Honglei Zhuang, Zhen Qin, Jinsung Yoon, Lanyu Shang, Jiawei Han, Dong Wang
IllumiCraft: Unified Geometry and Illumination Diffusion for Controllable Video Generation
Yuanze Lin, Yi-Wen Chen, Yi-Hsuan Tsai, Ronald Clark, Ming-Hsuan Yang
Improved Balanced Classification with Theoretically Grounded Loss Functions
Corinna Cortes, Mehryar Mohri, Yutao Zhong
Improved Best-of-Both-Worlds Regret for Bandits with Delayed Feedback
Ofir Schlisselberg, Tal Lancewicki, Peter Auer, Yishay Mansour
Improved Scaling Laws in Linear Regression via Data Reuse
Licong Lin, Jingfeng Wu, Peter L. Bartlett
Individual Regret in Cooperative Stochastic Multi-Armed Bandits
Idan Barnea, Tal Lancewicki, Yishay Mansour
Informed Correctors for Discrete Diffusion Models
Yixiu Zhao, Jiaxin Shi, Feng Chen, Shaul Druckmann, Lester Mackey, Scott Linderman
InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy
Vishnu Vinod, Krishna Pillutla, Abhradeep Thakurta
Isotropic Noise in Stochastic and Quantum Convex Optimization
Annie Marsden, Liam O’Carroll, Aaron Sidford, Chenyi Zhang
Kernel Density Steering: Inference-Time Scaling via Mode Seeking for Image Restoration
Yuyang Hu*, Kangfu Mei, Mojtaba Sahraee-Ardakan, Ulugbek S. Kamilov, Peyman Milanfar, Mauricio Delbracio
Learning Efficient Fuse-and-Refine for Feed-Forward 3D Gaussian Splatting
Yiming Wang, Lucy Chai, Xuan Luo, Michael Niemeyer, Manuel Lagunas, Stephen Lombardi, Siyu Tang, Tiancheng Sun
Large Stepsizes Accelerate Gradient Descent for Regularized Logistic Regression
Jingfeng Wu, Pierre Marion, Peter L. Bartlett
Learning Long Range Dependencies Through Time Reversal Symmetry Breaking
Guillaume Pourcel, Maxence Ernoult
Learning Neural Exposure Fields for View Synthesis
Michael Niemeyer, Fabian Manhardt, Marie-Julie Rakotosaona, Michael Oechsle, Christina Tsalicoglou, Keisuke Tateno, Jonathan T. Barron, Federico Tombari
Length Generalization via Auxiliary Tasks
Pranjal Awasthi, Anupam Gupta, Ravi Kumar
LocDiff: Identifying Locations on Earth by Diffusing in the Hilbert Space
Zhangyu Wang, Zeping Liu, Jielu Zhang, Zhongliang Zhou, Qian Cao, Nemin Wu, Lan Mu, Yang Song, Yiqun Xie, Ni Lao, Gengchen Mai
Machine Unlearning Under Overparameterization
Jacob L. Block, Aryan Mokhtari, Sanjay Shakkottai
Marginal-Nonuniform PAC Learnability
Steve Hanneke, Shay Moran, Maximilian Thiessen
Martingale Posterior Neural Networks for Fast Sequential Decision Making
Gerardo Duran-Martin, Leandro Sánchez-Betancourt, Álvaro Cartea, Kevin Murphy
Matryoshka Pilot: Learning to Drive Black-Box LLMs with LLMs
Changhao Li, Yuchen Zhuang, Rushi Qiang, Haotian Sun, Hanjun Dai, Chao Zhang, Bo Dai
Mechanism Design via the Interim Relaxation
Kshipra Bhawalkar, Marios Mertzanidis, Divyarthi Mohan, Alexandros Psomas
Mind the GAP! The Challenges of Scale in Pixel-Based Deep Reinforcement Learning (see blog post)
Ghada Sokar, Pablo Samuel Castro
Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation
Sangmin Bae, Yujin Kim, Reza Bayat, Sungnyun Kim, Jiyoun Ha, Tal Schuster, Adam Fisch, Hrayr Harutyunyan, Ziwei Ji, Aaron Courville, Se-Young Yun
MLE-STAR: Machine Learning Engineering Agent via Search and Targeted Refinement (see blog post)
Jaehyun Nam*, Jinsung Yoon, Jiefeng Chen, Jinwoo Shin, Sercan Ö. Arik, Tomas Pfister
Multiclass Loss Geometry Matters for Generalization of Gradient Descent in Separable Classification
Matan Schliserman, Tomer Koren
Nearly-Linear Time and Massively Parallel Algorithms for 𝓀-anonymity
Kevin Aydin, Honghao Lin*, David P. Woodruff, Peilin Zhong
Nested Learning: The Illusion of Deep Learning Architectures (see blog post)
Ali Behrouz, Meisam Razaviyayn, Peilin Zhong, Vahab Mirrokni
No-Regret Online Autobidding Algorithms in First-Price Auctions
Yilin Li, Yuan Deng, Wei Tang, Hanrui Zhang
Noise Hypernetworks: Amortizing Test-Time Compute in Diffusion Models
Luca Eyring, Shyamgopal Karthik, Alexey Dosovitskiy, Nataniel Ruiz, Zeynep Akata
Non-stationary Bandit Convex Optimization: A Comprehensive Study
Xiaoqi Liu, Dorian Baudry, Julian Zimmert, Patrick Rebeschini, Arya Akhavan
Object-X: Learning to Reconstruct Multi-Modal 3D Object Representations
Gaia Di Lorenzo, Federico Tombari, Marc Pollefeys, Daniel Barath
On the Complexity of Finding Stationary Points in Nonconvex Simple Bilevel Optimization
Jincheng Cao, Ruichen Jiang, Erfan Yazdandoost Hamedani, Aryan Mokhtari
On the Emergence of Linear Analogies in Word Embeddings
Daniel J. Korchinski, Dhruva Karkada, Yasaman Bahri, Matthieu Wyart
On Union-Closedness of Language Generation
Steve Hanneke, Anay Mehrotra, Amin Karbasi, Grigoris Velegkas
Optimal Mistake Bounds for Transductive Online Learning
Zachary Chase, Steve Hanneke, Shay Moran, Jonathan Shafer
Optimal Rates in Continual Linear Regression via Increasing Regularization
Ran Levinstein, Amit Attia, Matan Schliserman, Uri Sherman, Tomer Koren, Daniel Soudry, Itay Evron
Path-Specific Effects for Pulse-Oximetry Guided Decisions in Critical Care
Kevin Zhang, Yonghan Jung, Divyat Mahajan, Karthikeyan Shanmugam, Shalmali Joshi
Predictive Coding Enhances Meta-RL to Achieve Interpretable Bayes-Optimal Belief Representation Under Partial Observability
Po-Chen Kuo, Han Hou, Will Dabney, Edgar Y. Walker
Principled Model Routing for Unknown Mixtures of Source Domains
Christoph Dann, Yishay Mansour, Teodor V. Marinov, Mehryar Mohri
Privacy Reasoning in Ambiguous Contexts
Ren Yi, Octavian Suciu, Adrià Gascón, Sarah Meiklejohn, Eugene Bagdasarian, Marco Gruteser
Private Geometric Median in Nearly-Linear Time
Syamantak Kumar, Daogao Liu, Kevin Tian, Chutong Yang
Probably Approximately Precision and Recall Learning
Lee Cohen, Yishay Mansour, Shay Moran, Han Shao
ProDyG: Progressive Dynamic Scene Reconstruction via Gaussian Splatting from Monocular Videos
Shi Chen, Erik Sandström, Sandro Lombardi, Siyuan Li, Martin R. Oswald
Provable Meta-Learning with Low-Rank Adaptations
Jacob L. Block, Sundararajan Srinivasan, Liam Collins, Aryan Mokhtari, Sanjay Shakkottai
Quantifying Cross-Modality Memorization in Vision-Language Models
Yuxin Wen*, Yangsibo Huang, Tom Goldstein, Ravi Kumar, Badih Ghazi, Chiyuan Zhang
RAT: Bridging RNN Efficiency and Attention Accuracy via Chunk-Based Sequence Modeling
Xiuying Wei, Anunay Yadav, Razvan Pascanu, Caglar Gulcehre
Recursive Inference Scaling: A Winning Path to Scalable Inference in Language and Multimodal Systems
Ibrahim Alabdulmohsin, Xiaohua Zhai
REINFORCE Converges to Optimal Policies with Any Learning Rate
Samuel Robertson, Thang D. Chu, Bo Dai, Dale Schuurmans, Csaba Szepesvári, Jincheng Mei
Reinforcement Learning with Backtracking Feedback
Bilgehan Sel*, Vaishakh Keshava (GDM), Phillip Wallis, Lukas Rutishauser, Ming Jin, Dingcheng Li
Rendering-Aware Reinforcement Learning for Vector Graphics Generation
Juan A. Rodriguez, Haotian Zhang, Abhay Puri, Aarash Feizi, Rishav Pramanik, Pascal Wichmann, Arnab Mondal, Mohammad Reza Samsami, Rabiul Awal, Perouz Taslakian, Spandana Gella, Sai Rajeswar, David Vazquez, Christopher Pal, Marco Pedersoli
Replicable Online Pricing
Kiarash Banihashem, MohammadHossein Bateni, Hossein Esfandiari, Samira Goudarzi, MohammadTaghi Hajiaghayi
Robust and Diverse Multi-Agent Learning via Rational Policy Gradient
Niklas Lauffer, Ameesh Shah, Micah Carroll, Sanjit A. Seshia, Stuart Russell, Michael Dennis
Robust Contextual Pricing
Anupam Gupta, Guru Guruganesh, Renato Paes Leme, Jon Schneider
Robust LLM Alignment via Distributionally Robust Direct Preference Optimization
Zaiyan Xu, Sushil Vemuri, Kishan Panaganti, Dileep Kalathil, Rahul Jain, Deepak Ramachandran
ROGR: Relightable 3D Objects Using Generative Relighting
Jiapeng Tang, Matthew Lavine, Dor Verbin, Stephan J. Garbin, Matthias Nießner, Ricardo Martin Brualla, Pratul P. Srinivasan, Philipp Henzler
Sampling 3D Molecular Conformers with Diffusion Transformers
J. Thorben Frank, Winfried Ripken, Gregor Lied, Klaus Robert Müller, Oliver T. Unke, Stefan Chmiela
Scalable In-context Ranking with Generative Models
Nilesh Gupta, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Inderjit Dhillon, Felix Yu
Scaling Embedding Layers in Language Models
Da Yu, Edith Cohen, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Daogao Liu, Chiyuan Zhang
Scaling Image Geo-Localization to Continent Level
Philipp Lindenberger*, Paul-Edouard Sarlin, Jan Hosang, Marc Pollefeys, Simon Lynen, Eduard Trulls
Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing
Adel Javanmard, Rudrajit Das, Alessandro Epasto, Vahab Mirrokni
Self-Improving Embodied Foundation Models
Seyed Kamyar Seyed Ghasemipour*, Ayzaan Wahid, Jonathan Tompson, Pannag Sanketi, Igor Mordatch
SensorLM: Learning the Language of Wearable Sensors (see blog post)
Yuwei Zhang, Kumar Ayush, Siyuan Qiao, A. Ali Heydari, Girish Narayanswamy*, Maxwell A. Xu*, Ahmed A. Metwally, Shawn Xu, Jake Garrison, Xuhai Xu, Tim Althoff, Yun Liu, Pushmeet Kohli, Jiening Zhan, Mark Malhotra, Shwetak Patel, Cecilia Mascolo, Xin Liu, Daniel McDuff, Yuzhe Yang
Sequentially Auditing Differential Privacy
Tomás González, Mateo Dulce Rubio, Aaditya Ramdas, Mónica Ribero
Spark Transformer: Reactivating Sparsity in\nTransformer FFN and Attention
Chong You, Kan Wu*, Zhipeng Jia*, Lin Chen, Srinadh Bhojanapalli, Jiaxian Guo, Utku Evci, Jan Wassenberg, Praneeth Netrapalli, Jeremiah J. Willcock, Suvinay Subramanian, Felix Chern, Alek Andreev, Shreya Pathak, Felix Yu, Prateek Jain, Henry M. Levy, David E. Culler, Sanjiv Kumar
Sparse Gaussian Processes: Structured Approximations and Power-EP Revisited
Thang D. Bui, Michalis K. Titsias
SpectraLDS: Provable Distillation for Linear Dynamical Systems
Devan Shah, Shlomo Fortgang, Sofiia Druchyna, Elad Hazan
SPRINT: Enabling Interleaved Planning and Parallelized Execution in Reasoning Models
Emil Biju, Shayan Talaei, Zhemin Huang, Mohammadreza Pourreza, Azalia Mirhoseini, Amin Saberi
Stable Cinemetrics : Structured Taxonomy and Evaluation for Professional Video Generation
Agneet Chatterjee, Rahim Entezari, Maksym Zhuravinskyi, Max Lapin, Reshinth Adithyan, Amit Raj, Chitta Baral, Yezhou Yang, Varun Jampani
SWE-SQL: Illuminating LLM Pathways to Solve User SQL Issues in Real-World Applications
Jinyang Li, Xiaolong Li, Ge Qu, Per Jacobsson, Bowen Qin, Binyuan Hui, Shuzheng Si, Nan Huo, Xiaohan Xu, Yue Zhang, Ziwei Tang, Yuanshuai Li, Florensia Widjaja, Xintong Zhu, Feige Zhou, Yongfeng Huang, Yannis Papakonstantinou, Fatma Ozcan, Chenhao Ma, Reynold Cheng
Synthesize Privacy-Preserving High-Resolution Images via Private Textual Intermediaries
Haoxiang Wang, Zinan Lin, Da Yu, Huishuai Zhang
Temporal Chain of Thought: Long-Video Understanding by Thinking in Frames
Anurag Arnab, Ahmet Iscen, Mathilde Caron, Alireza Fathi, Cordelia Schmid
The Cost of Compression: Tight Quadratic Black-Box Attacks on Sketches for ℓ2 Norm Estimation
Sara Ahmadian, Edith Cohen, Uri Stemmer
The Emergence of Sparse Attention: Impact of Data Distribution and Benefits of Repetition
Nicolas Zucchet, Francesco D’Angelo, Andrew Lampinen, Stephanie Chan
Tight Bounds for Answering Adaptively Chosen Concentrated Queries
Emma Rapoport, Edith Cohen, Uri Stemmer
Titans: Learning to Memorize at Test Time
Ali Behrouz, Peilin Zhong, Vahab Mirrokni
Tracing the Representation Geometry of Language Models from Pretraining to Post-Training
Melody Zixuan Li, Kumar Krishna Agrawal, Arna Ghosh, Komal Kumar Teru, Adam Santoro, Guillaume Lajoie, Blake A. Richards
Training-Free Online Video Step Grounding
Luca Zanella, Massimiliano Mancini, Yiming Wang, Alessio Tonioni, Elisa Ricci
UMAMI: Unifying Masked Autoregressive Models and Deterministic Rendering for View Synthesis
Tung Le, Tuan Pham, Tung Nguyen, Deying Kong, Xiaohui Xie, Stephan Mandt
Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks
Gavin McCracken, Gabriela Moisescu-Pareja, Vincent Létourneau, Doina Precup, Jonathan Love
Understanding Challenges to the Interpretation of\nDisaggregated Evaluations of Algorithmic Fairness
Stephen R. Pfohl, Natalie Harris, Chirag Nagpal, David Madras, Vishwali Mhasawade, Olawale Salaudeen, Awa Dieng, Shannon Sequeira, Santiago Arciniegas, Lillian Sung, Nnamdi Ezeanochie, Heather Cole-Lewis, Katherine Heller, Sanmi Koyejo, Alexander D’Amour
Understanding Outer Optimizers in Local SGD:\nLearning Rates, Momentum, and Acceleration
Ahmed Khaled*, Satyen Kale*, Arthur Douillard, Chi Jin, Rob Fergus, Manzil Zaheer*
Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy
Bogdan Kulynych, Juan Felipe Gomez, Georgios Kaissis, Jamie Hayes, Borja Balle, Flavio P. Calmon, Jean Louis Raisaro
Universal Sequence Preconditioning
Annie Marsden, Elad Hazan
VESSA: Video-based objEct-centric Self-Supervised Adaptation for Visual Foundation Models
Jesimon Barreto, Carlos Caetano, André Araujo, William Robson Schwartz
When Do Transformers Outperform Feedforward and Recurrent Networks? A Statistical Perspective
Alireza Mousavi-Hosseini, Clayton Sanford, Denny Wu, Murat A. Erdogdu
Zero-Shot Performance Prediction for Probabilistic Scaling Laws
Viktoria Schram, Markus Hiller, Daniel Beck, Trevor Cohn
