Papers
Active Fine-Tuning of Multi-Task Policies
Marco Bagatella, Jonas Hübotter, Georg Martius et al.
Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning
Seungho Baek, Taegeon Park, Jongchan Park et al.
Positional Attention: Expressivity and Learnability of Algorithmic Computation
Artur Back De Luca, George Giapitzakis, Shenghao Yang et al.
Layer-wise Alignment: Examining Safety Alignment Across Image Encoder Layers in Vision Language Models
Saketh Bachu, Erfan Shayegani, Rohit Lal et al.
A Parametric Contextual Online Learning Theory of Brokerage
François Bachoc, Tommaso Cesari, Roberto Colomboni
FlexTok: Resampling Images into 1D Token Sequences of Flexible Length
Roman Bachmann, Jesse Allardice, David Mizrahi et al.
Sampling Binary Data by Denoising through Score Functions
Francis Bach, Saeed Saremi
Contract Design Under Approximate Best Responses
Francesco Bacchiocchi, Jiarui Gan, Matteo Castiglioni et al.
Adaptive Estimation and Learning under Temporal Distribution Shift
Dheeraj Baby, Yifei Tang, Hieu Duy Nguyen et al.
Near-Optimal Decision Trees in a SPLIT Second
Varun Babbar, Hayden Mctavish, Cynthia Rudin et al.
Visual Graph Arena: Evaluating Visual Conceptualization of Vision and Multimodal Large Language Models
Zahra Babaiee, Peyman Kiasari, Daniela Rus et al.
Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective
Steve Azzolin, Sagar Malhotra, Andrea Passerini et al.
The Global Convergence Time of Stochastic Gradient Descent in Non-Convex Landscapes: Sharp Estimates via Large Deviations
Waı̈ss Azizian, Franck Iutzeler, Jerome Malick et al.
PAC Learning with Improvements
Idan Attias, Avrim Blum, Keziah Naggita et al.
Faster Stochastic Optimization with Arbitrary Delays via Adaptive Asynchronous Mini-Batching
Amit Attia, Ofir Gaash, Tomer Koren
Risk and cross validation in ridge regression with correlated samples
Alexander Atanasov, Jacob A Zavatone-Veth, Cengiz Pehlevan
Autoformulation of Mathematical Optimization Models Using LLMs
Nicolás Astorga, Tennison Liu, Yuanzhang Xiao et al.
Improving the Scaling Laws of Synthetic Data with Deliberate Practice
Reyhane Askari-Hemmat, Mohammad Pezeshki, Elvis Dohmatob et al.
Faster Rates for Private Adversarial Bandits
Hilal Asi, Vinod Raman, Kunal Talwar
Tracking The Best Expert Privately
Hilal Asi, Vinod Raman, Aadirupa Saha
LLMs can see and hear without any training
Kumar Ashutosh, Yossi Gandelsman, Xinlei Chen et al.
Gridded Transformer Neural Processes for Spatio-Temporal Data
Matthew Ashman, Cristiana Diaconu, Eric Langezaal et al.
Aligning LLMs by Predicting Preferences from User Writing Samples
Stéphane Aroca-Ouellette, Natalie Mackraz, Barry-John Theobald et al.
Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model
Kaito Ariu, Alexandre Proutiere, Se-Young Yun
Online Conformal Prediction via Online Optimization
Felipe Areces, Christopher Mohri, Tatsunori Hashimoto et al.