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Increasingly, model compression techniques enable large language models (LLMs) to be deployed in real-world applications.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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Optimal brain damage
Yann LeCun, John Denker, and Sara Solla. 1989 · 1989
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Optimal brain surgeon and general network pruning
Babak Hassibi, David G Stork, and Gregory J Wolff. 1993 · 1993
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Vader: A parsimonious rule-based model for sentiment analysis of social media text
Clayton Hutto and Eric Gilbert. 2014 · 2014
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Demographic dialectal variation in social media: A case study of African-American English
Su Lin Blodgett, Lisa Green, and Brendan O’Connor. 2016 · 2016
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Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2016 · 2016
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Toxic comment classification challenge
CJ Adams, Jeffrey Sorensen, Julia Elliott, Lucas Dixon, nithum Mark McDonald, and Will Cukierski. 2017 · 2017
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The trouble with bias
Kate Crawford. 2017 · 2017
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Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
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Openwebtext corpus
Aaron Gokaslan, Vanya Cohen, Ellie Pavlick, and Stefanie Tellex. 2019 · 2019
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Albert: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2019 · 2019
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The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng. 2019 · 2019
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Language (technology) is power: A critical survey of “bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, and Hanna Wallach. 2020 · 2020
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Realtoxicityprompts: Evaluating neural toxic degeneration in language models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A Smith. 2020 · 2020
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2020 · 2020
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Unqovering stereotyping biases via underspecified questions
Tao Li, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, and Vivek Srikumar. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters
Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase, and Yuxiong He. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
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Bold: Dataset and metrics for measuring biases in open-ended language generation
Jwala Dhamala, Tony Sun, Varun Kumar, Satyapriya Krishna, Yada Pruksachatkun, Kai-Wei Chang, and Rahul Gupta. 2021 · 2021
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On language models for creoles
Heather Lent, Emanuele Bugliarello, Miryam de Lhoneux, Chen Qiu, and Anders Søgaard. 2021 · 2021
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Truthfulqa: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans. 2021 · 2021
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Accelerating inference with sparsity using the nvidia ampere architecture and nvidia tensorrt
Team Nvidia. 2021 · 2021
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Gpt3. int8 (): 8-bit matrix multiplication for transformers at scale
Tim Dettmers, Mike Lewis, Younes Belkada, and Luke Zettlemoyer. 2022 · 2022
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Gptq: Accurate post-training quantization for generative pre-trained transformers
Elias Frantar, Saleh Ashkboos, Torsten Hoefler, and Dan Alistarh. 2022 · 2022
Cited alongside, same era.
Toxigen: A large-scale machine-generated dataset for adversarial and implicit hate speech detection
Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, Maarten Sap, Dipankar Ray, and Ece Kamar. 2022 · 2022
Cited alongside, same era.
Gmp*: Well-tuned gradual magnitude pruning can outperform most bert-pruning methods
Eldar Kurtic and Dan Alistarh. 2022 · 2022
Cited alongside, same era.
Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity
Yao Lu, Max Bartolo, Alastair Moore, Sebastian Riedel, and Pontus Stenetorp. 2022 · 2022
Cited alongside, same era.
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
Mingxue Xu, Yao Lei Xu, and Danilo P Mandic. 2023 · 2023
Later among the works it cites.
Context-aware decoding reduces hallucination in query-focused summarization
Zhichao Xu. 2023 · 2023
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A lightweight constrained generation alternative for query-focused summarization
Zhichao Xu and Daniel Cohen. 2023 · 2023
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Junk dna hypothesis: A task-centric angle of llm pre-trained weights through sparsity
Lu Yin, Shiwei Liu, Ajay Jaiswal, Souvik Kundu, and Zhangyang Wang. 2023 · 2023
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Judging LLM-as-a-judge with MT-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023 · 2023
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Cited alongside, same era.
“I’m sorry to hear that”: Finding new biases in language models with a holistic descriptor dataset
Eric Michael Smith, Melissa Hall, Melanie Kambadur, Eleonora Presani, and Adina Williams. 2022 · 2022
Cited alongside, same era.
Measuring representational harms in image captioning
Angelina Wang, Solon Barocas, Kristen Laird, and Hanna Wallach. 2022 · 2022
Cited alongside, same era.
Structured pruning learns compact and accurate models
Mengzhou Xia, Zexuan Zhong, and Danqi Chen. 2022 · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
Cited alongside, same era.
Fairness and machine learning: Limitations and opportunities
Solon Barocas, Moritz Hardt, and Arvind Narayanan. 2023 · 2023
Cited alongside, same era.
Beyond size: How gradients shape pruning decisions in large language models
Rocktim Jyoti Das, Liqun Ma, and Zhiqiang Shen. 2023 · 2023
Cited alongside, same era.
Using large language models in psychology
Dorottya Demszky, Diyi Yang, David S Yeager, Christopher J Bryan, Margarett Clapper, Susannah Chandhok, Johannes C Eichstaedt, Cameron Hecht, Jeremy Jamieson, Meghann Johnson, et al. 2023 · 2023
Cited alongside, same era.
Later among the works it cites.
A survey on model compression for large language models
Xunyu Zhu, Jian Li, Yong Liu, Can Ma, and Weiping Wang. 2023 · 2023
Later among the works it cites.
Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2024 · 2024
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An empirical investigation of matrix factorization methods for pre-trained transformers
Ashim Gupta, Sina Mahdipour Saravani, P Sadayappan, and Vivek Srikumar. 2024 · 2024
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Dialect prejudice predicts ai decisions about people’s character, employability, and criminality
Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky, and Sharese King. 2024 · 2024
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Decoding compressed trust: Scrutinizing the trustworthiness of efficient llms under compression
Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie, Kelsey Lieberman, James Diffenderfer, Brian Bartoldson, Ajay Jaiswal, Kaidi Xu, et al. 2024 · 2024
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Natural language processing for dialects of a language: A survey
Aditya Joshi, Raj Dabre, Diptesh Kanojia, Zhuang Li, Haolan Zhan, Gholamreza Haffari, and Doris Dippold. 2024 · 2024
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Awq: Activation-aware weight quantization for llm compression and acceleration
Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Wei-Ming Chen, Wei-Chen Wang, Guangxuan Xiao, Xingyu Dang, Chuang Gan, and Song Han. 2024 · 2024
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Kivi: A tuning-free asymmetric 2bit quantization for kv cache
Zirui Liu, Jiayi Yuan, Hongye Jin, Shaochen Zhong, Zhaozhuo Xu, Vladimir Braverman, Beidi Chen, and Xia Hu. 2024 · 2024
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Capabilities of gemini models in medicine
Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, et al. 2024 · 2024
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Dolma: An open corpus of three trillion tokens for language model pretraining research
Luca Soldaini, Rodney Kinney, Akshita Bhagia, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi Chandu, Jennifer Dumas, Yanai Elazar, et al. 2024 · 2024
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A simple and effective pruning approach for large language models
Mingjie Sun, Zhuang Liu, Anna Bair, and J Zico Kolter. 2024 · 2024
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An in-depth investigation of user response simulation for conversational search
Zhenduo Wang, Zhichao Xu, Vivek Srikumar, and Qingyao Ai. 2024 · 2024
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Sheared LLaMA: Accelerating language model pre-training via structured pruning
Mengzhou Xia, Tianyu Gao, Zhiyuan Zeng, and Danqi Chen. 2024 · 2024
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Rankmamba: benchmarking mamba’s document ranking performance in the era of transformers
Zhichao Xu. 2024 · 2024
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In-context example ordering guided by label distributions
Zhichao Xu, Daniel Cohen, Bei Wang, and Vivek Srikumar. 2024 · 2024
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Multi-dimensional evaluation of empathetic dialog responses
Zhichao Xu and Jiepu Jiang. 2024 · 2024
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Leanquant: Accurate large language model quantization with loss-error-aware grid
Tianyi Zhang and Anshumali Shrivastava. 2024 · 2024
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Kv cache is 1 bit per channel: Efficient large language model inference with coupled quantization
Tianyi Zhang, Jonah Yi, Zhaozhuo Xu, and Anshumali Shrivastava. 2024 · 2024
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Reducing the carbon impact of generative ai inference (today and in 2035)
Andrew A Chien, Liuzixuan Lin, Hai Nguyen, Varsha Rao, Tristan Sharma, and Rajini Wijayawardana. 2023 · 2035
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BBQ: A hand-built bias benchmark for question answering
Alicia Parrish, Angelica Chen, Nikita Nangia, Vishakh Padmakumar, Jason Phang, Jana Thompson, Phu Mon Htut, and Samuel Bowman. 2022 · 2086
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