Papers
214 papers found
A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition
Connor Malone, Somayeh Hussaini, Tobias Fischer et al.
IDEATOR: Jailbreaking and Benchmarking Large Vision-Language Models Using Themselves
Ruofan Wang, Juncheng Li, Yixu Wang et al.
One Encoder to Rule them All: Representation Learning for Model-free Visual Reinforcement Learning using Fourier Neural Operators
Parag Dutta, Mohd Ayyoob, Shalabh Bhatnagar et al.
TurboVSR: Fantastic Video Upscalers and Where to Find Them
Zhongdao Wang, Guodongfang Zhao, Jingjing Ren et al.
Rethinking Discrete Tokens: Treating Them as Conditions for Continuous Autoregressive Image Synthesis
Peng Zheng, Junke Wang, Yi Chang et al.
Fantastic Generalization Measures and Where to Find Them
Yiding Jiang*, Behnam Neyshabur*, Hossein Mobahi et al.
Multiplicative Interactions and Where to Find Them
Siddhant M. Jayakumar, Wojciech M. Czarnecki, Jacob Menick et al.
Learning from others' mistakes: Avoiding dataset biases without modeling them
Victor Sanh, Thomas Wolf, Yonatan Belinkov et al.
No One Representation to Rule Them All: Overlapping Features of Training Methods
Raphael Gontijo-Lopes, Yann Dauphin, Ekin Dogus Cubuk
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems
Yihao Feng, Shentao Yang, Shujian Zhang et al.
Language Models Can Teach Themselves to Program Better
Patrick Haluptzok, Matthew Bowers, Adam Tauman Kalai
Impossibly Good Experts and How to Follow Them
Aaron Walsman, Muru Zhang, Sanjiban Choudhury et al.
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model
Karsten Roth, Lukas Thede, A. Sophia Koepke et al.
RAIN: Your Language Models Can Align Themselves without Finetuning
Yuhui Li, Fangyun Wei, Jinjing Zhao et al.
LLMs Can Plan Only If We Tell Them
Bilgehan Sel, Ruoxi Jia, Ming Jin
Looking Inward: Language Models Can Learn About Themselves by Introspection
Felix Jedidja Binder, James Chua, Tomek Korbak et al.
Fantastic Copyrighted Beasts and How (Not) to Generate Them
Luxi He, Yangsibo Huang, Weijia Shi et al.
Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them
Anh Tuan Bui, Thuy-Trang Vu, Long Tung Vuong et al.
Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
Wouter Kool, Herke Van Hoof, Max Welling
One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control
Wenlong Huang, Igor Mordatch, Deepak Pathak
Hyperparameters in Reinforcement Learning and How To Tune Them
Theresa Eimer, Marius Lindauer, Roberta Raileanu
Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods
Aleksandr Shevchenko, Kevin Kögler, Hamed Hassani et al.
Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning
Hongzuo Xu, Yijie Wang, Juhui Wei et al.