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Neel Jain
Neel Jain
在 umd.edu 的电子邮件经过验证 - 首页
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Baseline Defenses for Adversarial Attacks Against Aligned Language Models
N Jain, A Schwarzschild, Y Wen, G Somepalli, J Kirchenbauer, P Chiang, ...
arXiv preprint arXiv:2309.00614, 2023
173*2023
Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery
Y Wen, N Jain, J Kirchenbauer, M Goldblum, J Geiping, T Goldstein
Conference on Neural Information Processing Systems (NeurIPS) 2023, 2023
1552023
NEFTune: Noisy embeddings improve instruction finetuning
N Jain, P yeh Chiang, Y Wen, J Kirchenbauer, HM Chu, G Somepalli, ...
The Twelfth International Conference on Learning Representations, 2023
48*2023
Bring Your Own Data! Self-Sensitivity Evaluation for Large Language Models
N Jain, K Saifullah, Y Wen, J Kirchenbauer, M Shu, A Saha, M Goldblum, ...
First Conference on Language Modeling, 0
18*
Transformers Can Do Arithmetic with the Right Embeddings
S McLeish, A Bansal, A Stein, N Jain, J Kirchenbauer, BR Bartoldson, ...
ICML 2024 Workshop on LLMs and Cognition, 2024
7*2024
Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs
A Hans, Y Wen, N Jain, J Kirchenbauer, H Kazemi, P Singhania, S Singh, ...
arXiv preprint arXiv:2406.10209, 2024
2*2024
LiveBench: A Challenging, Contamination-Free LLM Benchmark
C White, S Dooley, M Roberts, A Pal, B Feuer, S Jain, R Shwartz-Ziv, ...
arXiv preprint arXiv:2406.19314, 2024
12024
GenQA: Generating Millions of Instructions from a Handful of Prompts
J Chen, R Qadri, Y Wen, N Jain, J Kirchenbauer, T Zhou, T Goldstein
arXiv preprint arXiv:2406.10323, 2024
12024
Multi-color forcing in graphs
C Bozeman, PE Harris, N Jain, B Young, T Yu
Graphs and Combinatorics 36 (6), 1855-1868, 2020
2020
How to Do a Vocab Swap? A Study of Embedding Replacement for Pre-trained Transformers
N Jain, J Kirchenbauer, J Geiping, T Goldstein
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