Papers
AUTOCIRCUIT-RL: Reinforcement Learning-Driven LLM for Automated Circuit Topology Generation
Prashanth Vijayaraghavan, Luyao Shi, Ehsan Degan et al.
Deep Sturm–Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions
David Vigouroux, Joseba Dalmau, Louis Béthune et al.
IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic
Stefano Viel, Luca Viano, Volkan Cevher
Language Models over Canonical Byte-Pair Encodings
Tim Vieira, Tianyu Liu, Clemente Pasti et al.
From Language Models over Tokens to Language Models over Characters
Tim Vieira, Benjamin Lebrun, Mario Giulianelli et al.
BaxBench: Can LLMs Generate Correct and Secure Backends?
Mark Vero, Niels Mündler, Victor Chibotaru et al.
Positional Encoding meets Persistent Homology on Graphs
Yogesh Verma, Amauri H Souza, Vikas K Garg
GRAIL: Graph Edit Distance and Node Alignment using LLM-Generated Code
Samidha Verma, Arushi Goyal, Ananya Mathur et al.
Improving Diversity in Language Models: When Temperature Fails, Change the Loss
Alexandre Verine, Florian Le Bronnec, Kunhao Zheng et al.
Automated Benchmark Generation for Repository-Level Coding Tasks
Konstantinos Vergopoulos, Mark Niklas Mueller, Martin Vechev
Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models
Siddarth Venkatraman, Mohsin Hasan, Minsu Kim et al.
Softmax is not Enough (for Sharp Size Generalisation)
Petar Veličković, Christos Perivolaropoulos, Federico Barbero et al.
PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models
Alejandro Velez-Arce, Marinka Zitnik
Approximate Forest Completion and Learning-Augmented Algorithms for Metric Minimum Spanning Trees
Nate Veldt, Thomas Stanley, Benjamin W Priest et al.
Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision Transformers
Lokesh Veeramacheneni, Moritz Wolter, Hilde Kuehne et al.
Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis
Christophe Vauthier, Anna Korba, Quentin Mérigot
Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster
Sharan Vaswani, Reza Babanezhad Harikandeh
Covered Forest: Fine-grained generalization analysis of graph neural networks
Antonis Vasileiou, Ben Finkelshtein, Floris Geerts et al.
Teaching Transformers Causal Reasoning through Axiomatic Training
Aniket Vashishtha, Abhinav Kumar, Atharva Pandey et al.
Learning In-context n-grams with Transformers: Sub-n-grams Are Near-Stationary Points
Aditya Varre, Gizem Yüce, Nicolas Flammarion
Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization
Shira Vansover-Hager, Tomer Koren, Roi Livni
AutoCATE: End-to-End, Automated Treatment Effect Estimation
Toon Vanderschueren, Tim Verdonck, Mihaela Van Der Schaar et al.
Dimension-Independent Rates for Structured Neural Density Estimation
Robert A. Vandermeulen, Wai Ming Tai, Bryon Aragam
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection
Moritz Vandenhirtz, Julia E Vogt
When to Forget? Complexity Trade-offs in Machine Unlearning
Martin Van Waerebeke, Marco Lorenzi, Giovanni Neglia et al.