Papers
Optimal transport-based conformal prediction
Gauthier Thurin, Kimia Nadjahi, Claire Boyer
MixMin: Finding Data Mixtures via Convex Minimization
Anvith Thudi, Evianne Rovers, Yangjun Ruan et al.
NTK-DFL: Enhancing Decentralized Federated Learning in Heterogeneous Settings via Neural Tangent Kernel
Gabriel Thompson, Kai Yue, Chau-Wai Wong et al.
Hidden No More: Attacking and Defending Private Third-Party LLM Inference
Rahul Krishna Thomas, Louai Zahran, Erica Choi et al.
What can large language models do for sustainable food?
Anna Thomas, Adam Yee, Andrew Mayne et al.
Comparing Few to Rank Many: Active Human Preference Learning Using Randomized Frank-Wolfe Method
Kiran Koshy Thekumparampil, Gaurush Hiranandani, Kousha Kalantari et al.
WikiBigEdit: Understanding the Limits of Lifelong Knowledge Editing in LLMs
Lukas Thede, Karsten Roth, Matthias Bethge et al.
Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment
Harrish Thasarathan, Julian Forsyth, Thomas Fel et al.
Geometric Contact Flows: Contactomorphisms for Dynamics and Control
Andrea Testa, Søren Hauberg, Tamim Asfour et al.
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems
Manan Tayal, Aditya Singh, Shishir Kolathaya et al.
Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks
Nurbek Tastan, Samuel Horváth, Karthik Nandakumar
Deep Bayesian Filter for Bayes-Faithful Data Assimilation
Yuta Tarumi, Keisuke Fukuda, Shin-Ichi Maeda
Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks’ Internal Representations
Aditya Taparia, Som Sagar, Ransalu Senanayake
Unisoma: A Unified Transformer-based Solver for Multi-Solid Systems
Shilong Tao, Zhe Feng, Haonan Sun et al.
(How) Can Transformers Predict Pseudo-Random Numbers?
Tao Tao, Darshil Doshi, Dayal Singh Kalra et al.
S2-Track: A Simple yet Strong Approach for End-to-End 3D Multi-Object Tracking
Tao Tang, Lijun Zhou, Pengkun Hao et al.
Optimizing Language Models for Inference Time Objectives using Reinforcement Learning
Yunhao Tang, Kunhao Zheng, Gabriel Synnaeve et al.
PepTune: De Novo Generation of Therapeutic Peptides with Multi-Objective-Guided Discrete Diffusion
Sophia Tang, Yinuo Zhang, Pranam Chatterjee
Multi-Session Budget Optimization for Forward Auction-based Federated Learning
Xiaoli Tang, Han Yu, Zengxiang Li et al.
Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model
Kaiwen Tang, Zhanglu Yan, Weng-Fai Wong
Controllable Data Generation with Hierarchical Neural Representations
Sheyang Tang, Xiaoyu Xu, Jiayan Qiu et al.
LOGO — Long cOntext aliGnment via efficient preference Optimization
Zecheng Tang, Zechen Sun, Juntao Li et al.
Efficient Heterogeneity-Aware Federated Active Data Selection
Ying-Peng Tang, Chao Ren, Xiaoli Tang et al.
Inference-Time Alignment of Diffusion Models with Direct Noise Optimization
Zhiwei Tang, Jiangweizhi Peng, Jiasheng Tang et al.