LED-Merging: Mitigating Safety-Utility Conflicts in Model Merging with Location-Election-Disjoint

Stochastic weight averaging in parallel: Large-batch training that generalizes well

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Vipul Gupta, Santiago Akle Serrano, and Dennis DeCoste. 2020 · 2001

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Striving for Simplicity: The All Convolutional Net

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Learning Important Features Through Propagating Activation Differences

Avanti Shrikumar, Peyton Greenside, and Anshul Kundaje. 2017 · 2017

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Axiomatic Attribution for Deep Networks

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SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY

Namhoon Lee, Thalaiyasingam Ajanthan, and Philip Torr. 2019 · 2019

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Are sixteen heads really better than one?

Paul Michel, Omer Levy, and Graham Neubig. 2019 · 2019

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Language models are few-shot learners

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A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI

Erico Tjoa and Cuntai Guan. 2020 · 2020

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Program synthesis with large language models

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Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, et al. 2021 · 2021

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Training verifiers to solve math word problems

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Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021 · 2021

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Measuring mathematical problem solving with the math dataset

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Ensemble of averages: Improving model selection and boosting performance in domain generalization

Devansh Arpit, Huan Wang, Yingbo Zhou, and Caiming Xiong. 2022 · 2022

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Fusing finetuned models for better pretraining

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Leshem Choshen, Elad Venezian, Noam Slonim, and Yoav Katz. 2022 · 2022

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Patching open-vocabulary models by interpolating weights

Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song, Hannaneh Hajishirzi, Simon Kornblith, Ali Farhadi, and Ludwig Schmidt. 2022 · 2022

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Training language models to follow instructions with human feedback

Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022

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Diverse weight averaging for out-of-distribution generalization

Alexandre Rame, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari, and Matthieu Cord. 2022 · 2022

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Qwen technical report

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Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, Binyuan Hui, Luo Ji, Mei Li, Junyang Lin, Runji Lin, Dayiheng Liu, Gao Liu, Chengqiang Lu, Keming Lu, Jianxin Ma, Rui Men, Xingzhang Ren, Xuancheng Ren, Chuanqi Tan, Sinan Tan, Jianhong Tu, Peng Wang, Shijie Wang, Wei Wang, Shengguang Wu, Benfeng Xu, Jin Xu, An Yang, Hao Yang, Jian Yang, Shusheng Yang, Yang Yao, Bowen Yu, Hongyi Yuan, Zheng Yuan, Jianwei Zhang, Xingxuan Zhang, Yichang Zhang, Zhenru Zhang, Chang Zhou, Jingren Zhou, Xiaohuan Zhou, and Tianhang Zhu. 2023 · 2023

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Discovering Latent Knowledge in Language Models Without Supervision

Collin Burns, Haotian Ye, Dan Klein, and Jacob Steinhardt. 2023 · 2023

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Breaking language barriers in multilingual mathematical reasoning: Insights and observations

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Nuo Chen, Zinan Zheng, Ning Wu, Ming Gong, Dongmei Zhang, and Jia Li. 2023 · 2023

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Sparsegpt: Massive language models can be accurately pruned in one-shot

Elias Frantar and Dan Alistarh. 2023 · 2023

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Lorahub: Efficient cross-task generalization via dynamic lora composition

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Chengsong Huang, Qian Liu, Bill Yuchen Lin, Tianyu Pang, Chao Du, and Min Lin. 2023 · 2023

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Mistral 7b

Original

Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2023 · 2023

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Dataless knowledge fusion by merging weights of language models

Xisen Jin, Xiang Ren, Daniel Preotiuc-Pietro, and Pengxiang Cheng. 2023 · 2023

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Efficient memory management for large language model serving with pagedattention

Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023

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Trustworthy llms: a survey and guideline for evaluating large language models’ alignment

Original

Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo, Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, and Hang Li. 2023 · 2023

Cited alongside, same era.

Wizardmath: Empowering mathematical reasoning for large language models via reinforced evol-instruct

Original

Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Jianguang Lou, Chongyang Tao, Xiubo Geng, Qingwei Lin, Shifeng Chen, and Dongmei Zhang. 2023 · 2023

Cited alongside, same era.

Can Neural Network Memorization Be Localized?

Aligner: Efficient alignment by learning to correct

Original

Jiaming Ji, Boyuan Chen, Hantao Lou, Donghai Hong, Borong Zhang, Xuehai Pan, Juntao Dai, Tianyi Qiu, and Yaodong Yang. 2024 · 2024

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Cade: Cosine annealing differential evolution for spiking neural network

Original

Runhua Jiang, Guodong Du, Shuyang Yu, Yifei Guo, Sim Kuan Goh, and Ho-Kin Tang. 2024 · 2024

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A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity

Original

Andrew Lee, Xiaoyan Bai, Itamar Pres, Martin Wattenberg, Jonathan K Kummerfeld, and Rada Mihalcea. 2024 · 2024

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The wmdp benchmark: Measuring and reducing malicious use with unlearning

Original

Nathaniel Li, Alexander Pan, Anjali Gopal, Summer Yue, Daniel Berrios, Alice Gatti, Justin D Li, Ann-Kathrin Dombrowski, Shashwat Goel, Long Phan, et al. 2024 · 2024

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