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Aligned Large Language Models (LLMs) showcase remarkable versatility, capable of handling diverse real-world tasks.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Glu variants improve transformer
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Adam: A method for stochastic optimization
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The legal consultation data and corpus of the thesis from China law network.Replication Data for: Design and research of legal consultation text classification system
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DuReader: a Chinese machine reading comprehension dataset from real-world applications
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Explicit inductive bias for transfer learning with convolutional networks
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Episodic memory in lifelong language learning
Cyprien de Masson D’Autume, Sebastian Ruder, Lingpeng Kong, and Dani Yogatama. 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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Experience replay for continual learning
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy Lillicrap, and Gregory Wayne. 2019 · 2019
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Repulsive attention: Rethinking multi-head attention as bayesian inference
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Ocnli: Original chinese natural language inference
Hai Hu, Kyle Richardson, Liang Xu, Lu Li, Sandra Kuebler, and Larry Moss. 2020 · 2020
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Emergent linguistic structure in artificial neural networks trained by self-supervision
Christopher D Manning, Kevin Clark, John Hewitt, Urvashi Khandelwal, and Omer Levy. 2020 · 2020
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TNT: Text normalization based pre-training of transformers for content moderation
Fei Tan, Yifan Hu, Changwei Hu, Keqian Li, and Kevin Yen. 2020 · 2020
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
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Jec-qa: A legal-domain question answering dataset
Haoxi Zhong, Chaojun Xiao, Cunchao Tu, Tianyang Zhang, Zhiyuan Liu, and Maosong Sun. 2020 · 2020
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Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al. 2021 · 2021
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A mathematical framework for transformer circuits
Nelson Elhage, Neel Nanda, Catherine Olsson, Tom Henighan, Nicholas Joseph, Ben Mann, Amanda Askell, Yuntao Bai, Anna Chen, Tom Conerly, et al. 2021 · 2021
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Wino-X: Multilingual Winograd schemas for commonsense reasoning and coreference resolution
Denis Emelin and Rico Sennrich. 2021 · 2021
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A framework for few-shot language model evaluation
Leo Gao, Jonathan Tow, Stella Biderman, Sid Black, Anthony DiPofi, Charles Foster, Laurence Golding, Jeffrey Hsu, Kyle McDonell, Niklas Muennighoff, Jason Phang, Laria Reynolds, Eric Tang, Anish Thite, Ben Wang, Kevin Wang, and Andy Zou. 2021 · 2021
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Transformer feed-forward layers are key-value memories
Mor Geva, Roei Schuster, Jonathan Berant, and Omer Levy. 2021 · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al. 2021 · 2021
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Continual mixed-language pre-training for extremely low-resource neural machine translation
Zihan Liu, Genta Indra Winata, and Pascale Fung. 2021b · 2021
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Continual learning in task-oriented dialogue systems
Andrea Madotto, Zhaojiang Lin, Zhenpeng Zhou, Seungwhan Moon, Paul Crook, Bing Liu, Zhou Yu, Eunjoon Cho, Pascale Fung, and Zhiguang Wang. 2021 · 2021
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Zero-infinity: Breaking the gpu memory wall for extreme scale deep learning
Samyam Rajbhandari, Olatunji Ruwase, Jeff Rasley, Shaden Smith, and Yuxiong He. 2021 · 2021
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A primer in bertology: What we know about how bert works
Anna Rogers, Olga Kovaleva, and Anna Rumshisky. 2021 · 2021
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BERT-beta: A proactive probabilistic approach to text moderation
Fei Tan, Yifan Hu, Kevin Yen, and Changwei Hu. 2021 · 2021
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Pretrained language model in continual learning: A comparative study
Tongtong Wu, Massimo Caccia, Zhuang Li, Yuan-Fang Li, Guilin Qi, and Gholamreza Haffari. 2021 · 2021
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Knowledge neurons in pretrained transformers
Damai Dai, Li Dong, Yaru Hao, Zhifang Sui, Baobao Chang, and Furu Wei. 2022 · 2022
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Editing models with task arithmetic
Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi. 2022 · 2022
Tora: A tool-integrated reasoning agent for mathematical problem solving
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yujiu Yang, Minlie Huang, Nan Duan, Weizhu Chen, et al. 2023 · 2023
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Quzhe Huang, Mingxu Tao, Zhenwei An, Chen Zhang, Cong Jiang, Zhibin Chen, Zirui Wu, and Yansong Feng. 2023 · 2023
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Multi-level contrastive learning for script-based character understanding
Dawei Li, Hengyuan Zhang, Yanran Li, and Shiping Yang. 2023a · 2023
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Logiqa 2.0—an improved dataset for logical reasoning in natural language understanding
Hanmeng Liu, Jian Liu, Leyang Cui, Zhiyang Teng, Nan Duan, Ming Zhou, and Yue Zhang. 2023 · 2023
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Tangent model composition for ensembling and continual fine-tuning
Tian Yu Liu and Stefano Soatto. 2023 · 2023
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Alleviating representational shift for continual fine-tuning
Shibo Jie, Zhi-Hong Deng, and Ziheng Li. 2022 · 2022
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Continual pre-training of language models
Zixuan Ke, Yijia Shao, Haowei Lin, Tatsuya Konishi, Gyuhak Kim, and Bing Liu. 2022 · 2022
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Blcu-icall at semeval-2022 task 1: Cross-attention multitasking framework for definition modeling
Cunliang Kong, Yujie Wang, Ruining Chong, Liner Yang, Hengyuan Zhang, Erhong Yang, and Yaping Huang. 2022b · 2022
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Branch-train-merge: Embarrassingly parallel training of expert language models
Margaret Li, Suchin Gururangan, Tim Dettmers, Mike Lewis, Tim Althoff, Noah A Smith, and Luke Zettlemoyer. 2022 · 2022
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Crosslingual generalization through multitask finetuning
Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts, Stella Biderman, Teven Le Scao, M Saiful Bari, Sheng Shen, Zheng-Xin Yong, Hailey Schoelkopf, Xiangru Tang, Dragomir Radev, Alham Fikri Aji, Khalid Almubarak, Samuel Albanie, Zaid Alyafeai, Albert Webson, Edward Raff, and Colin Raffel. 2022 · 2022
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Self-instruct: Aligning language model with self generated instructions
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2022 · 2022
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Crosslingual generalization through multitask finetuning
Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts, Stella Biderman, Teven Le Scao, M Saiful Bari, Sheng Shen, Zheng Xin Yong, Hailey Schoelkopf, et al. 2023 · 2023
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Proving test set contamination in black box language models
Yonatan Oren, Nicole Meister, Niladri Chatterji, Faisal Ladhak, and Tatsunori B Hashimoto. 2023 · 2023
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Fine-tuning or retrieval? comparing knowledge injection in llms
Oded Ovadia, Menachem Brief, Moshik Mishaeli, and Oren Elisha. 2023 · 2023
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Task-specific skill localization in fine-tuned language models
Abhishek Panigrahi, Nikunj Saunshi, Haoyu Zhao, and Sanjeev Arora. 2023 · 2023
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Baolin Peng, Chunyuan Li, Pengcheng He, Michel Galley, and Jianfeng Gao. 2023 · 2023
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Progressive prompts: Continual learning for language models
Anastasia Razdaibiedina, Yuning Mao, Rui Hou, Madian Khabsa, Mike Lewis, and Amjad Almahairi. 2023 · 2023
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Pretraining on the test set is all you need
Rylan Schaeffer. 2023 · 2023
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Continual diffusion: Continual customization of text-to-image diffusion with c-lora
James Seale Smith, Yen-Chang Hsu, Lingyu Zhang, Ting Hua, Zsolt Kira, Yilin Shen, and Hongxia Jin. 2023 · 2023
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A simple and effective pruning approach for large language models
Mingjie Sun, Zhuang Liu, Anna Bair, and J Zico Kolter. 2023 · 2023
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Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 2023 · 2023
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Yongqi Tong, Yifan Wang, Dawei Li, Sizhe Wang, Zi Lin, Simeng Han, and Jingbo Shang. 2023 · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023 · 2023
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Fingpt: Instruction tuning benchmark for open-source large language models in financial datasets
Neng Wang, Hongyang Yang, and Christina Wang. 2023b · 2023
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Language models are super mario: Absorbing abilities from homologous models as a free lunch
Le Yu, Bowen Yu, Haiyang Yu, Fei Huang, and Yongbin Li. 2023 · 2023
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Assisting language learners: Automated trans-lingual definition generation via contrastive prompt learning
Hengyuan Zhang, Dawei Li, Yanran Li, Chenming Shang, Chufan Shi, and Yong Jiang. 2023 · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al. 2023 · 2023
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ReLU strikes back: Exploiting activation sparsity in large language models
Seyed Iman Mirzadeh, Keivan Alizadeh-Vahid, Sachin Mehta, Carlo C del Mundo, Oncel Tuzel, Golnoosh Samei, Mohammad Rastegari, and Mehrdad Farajtabar. 2024 · 2024
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Can llms learn from previous mistakes? investigating llms’ errors to boost for reasoning
Yongqi Tong, Dawei Li, Sizhe Wang, Yujia Wang, Fei Teng, and Jingbo Shang. 2024 · 2024
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