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20232026
most citedBaseline Defenses for Adversarial Attacks Against Aligned Language Models

37 citations · 113 across the 18 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

cs.AI2023★ 4 cited

Perspectives on the State and Future of Deep Learning - 2023

Micah Goldblum, Anima Anandkumar, Richard Baraniuk +7

The goal of this series is to chronicle opinions and issues in the field of machine learning as they stand today and as they change over time. The plan is to host this survey perio…

cs.CV2023

Object Recognition as Next Token Prediction

Kaiyu Yue, Bor-Chun Chen, Jonas Geiping +3

We present an approach to pose object recognition as next token prediction. The idea is to apply a language decoder that auto-regressively predicts the text tokens from image embed…

cs.CV2023★ 26 cited

Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks

Micah Goldblum, Hossein Souri, Renkun Ni +10

Neural network based computer vision systems are typically built on a backbone, a pretrained or randomly initialized feature extractor. Several years ago, the default option was an…

cs.LG2023★ 7 cited

A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning

Valeriia Cherepanova, Roman Levin, Gowthami Somepalli +5

Academic tabular benchmarks often contain small sets of curated features. In contrast, data scientists typically collect as many features as possible into their datasets, and even…

cs.CV2023

A Simple and Efficient Baseline for Data Attribution on Images

Vasu Singla, Pedro Sandoval-Segura, Micah Goldblum +2

Data attribution methods play a crucial role in understanding machine learning models, providing insight into which training data points are most responsible for model outputs duri…

cs.CL2023★ 14 cited

NEFTune: Noisy Embeddings Improve Instruction Finetuning

Neel Jain, Ping-yeh Chiang, Yuxin Wen +10

We show that language model finetuning can be improved, sometimes dramatically, with a simple augmentation. NEFTune adds noise to the embedding vectors during training. Standard fi…

cs.LG2023★ 37 cited

Baseline Defenses for Adversarial Attacks Against Aligned Language Models

Neel Jain, Avi Schwarzschild, Yuxin Wen +7

As Large Language Models quickly become ubiquitous, it becomes critical to understand their security vulnerabilities. Recent work shows that text optimizers can produce jailbreakin…