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The development and evaluation of Large Language Models (LLMs) has primarily focused on their task-solving capabilities, with recent models even surpassing human performance in some areas.
Language models are few-shot learners
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On faithfulness and factuality in abstractive summarization
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Assessing Language Production in Children: Experimental Procedures
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Diversity in the lexical and syntactic abilities of fluent aphasic speakers
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Linguistic features of writing quality
Danielle S McNamara, Scott A Crossley, and Philip M McCarthy. 2010 · 2010
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Weisfeiler-lehman graph kernels
Nino Shervashidze, Pascal Schweitzer, Erik Jan van Leeuwen, Kurt Mehlhorn, and Karsten M. Borgwardt. 2011 · 2011
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Measuring lexical diversity in narrative discourse of people with aphasia
G Fergadiotis, HH Wright, and TM West. 2013 · 2013
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Findings of the 2014 workshop on statistical machine translation
Ondřej Bojar, Christian Buck, Christian Federmann, Barry Haddow, Philipp Koehn, Johannes Leveling, Christof Monz, Pavel Pecina, Matt Post, Herve Saint-Amand, Radu Soricut, Lucia Specia, and Aleš Tamchyna. 2014 · 2014
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Divergence in dialogue
Patrick GT Healey, Matthew Purver, and Christine Howes. 2014 · 2014
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A cross-linguistic perspective on syntactic complexity in l2 development: Syntactic elaboration and diversity
Bastien De Clercq and Alex Housen. 2017 · 2017
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Automatic measures to characterise verbal alignment in human-agent interaction
Guillaume Dubuisson Duplessis, Chloé Clavel, and Frédéric Landragin. 2017 · 2017
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Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2017 · 2017
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Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
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Hierarchical text generation and planning for strategic dialogue
Denis Yarats and Mike Lewis. 2018 · 2018
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Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Language gans falling short
Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, and Laurent Charlin. 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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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
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Stanza: A python natural language processing toolkit for many human languages
Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton, and Christopher D. Manning. 2020 · 2020
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COMET: A neural framework for MT evaluation
Ricardo Rei, Craig Stewart, Ana C Farinha, and Alon Lavie. 2020 · 2020
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Making monolingual sentence embeddings multilingual using knowledge distillation
Nils Reimers and Iryna Gurevych. 2020 · 2020
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Improving dialog evaluation with a multi-reference adversarial dataset and large scale pretraining
Ananya B. Sai, Akash Kumar Mohankumar, Siddhartha Arora, and Mitesh M. Khapra. 2020 · 2020
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Grakel: A graph kernel library in python
Giannis Siglidis, Giannis Nikolentzos, Stratis Limnios, Christos Giatsidis, Konstantinos Skianis, and Michalis Vazirgiannis. 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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XL-sum: Large-scale multilingual abstractive summarization for 44 languages
Tahmid Hasan, Abhik Bhattacharjee, Md. Saiful Islam, Kazi Mubasshir, Yuan-Fang Li, Yong-Bin Kang, M. Sohel Rahman, and Rifat Shahriyar. 2021 · 2021
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Mauve: Measuring the gap between neural text and human text using divergence frontiers
Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, and Zaid Harchaoui. 2021 · 2021
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Does human collaboration enhance the accuracy of identifying llm-generated deepfake texts?
Adaku Uchendu, Jooyoung Lee, Hua Shen, Thai Le, Dongwon Lee, et al. 2023 · 2023
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Ultrafeedback: Boosting language models with scaled ai feedback
Ganqu Cui, Lifan Yuan, Ning Ding, Guanming Yao, Bingxiang He, Wei Zhu, Yuan Ni, Guotong Xie, Ruobing Xie, Yankai Lin, et al. 2024 · 2024
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al. 2024 · 2024
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Bias and fairness in large language models: A survey
Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, Md Mehrab Tanjim, Sungchul Kim, Franck Dernoncourt, Tong Yu, Ruiyi Zhang, and Nesreen K. Ahmed. 2024 · 2024
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Trading off diversity and quality in natural language generation
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Towards robust NLG bias evaluation with syntactically-diverse prompts
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Help me write a poem - instruction tuning as a vehicle for collaborative poetry writing
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Of human criteria and automatic metrics: A benchmark of the evaluation of story generation
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Measuring and improving semantic diversity of dialogue generation
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Semantic diversity in dialogue with natural language inference
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Exploring precision and recall to assess the quality and diversity of LLMs
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Mapping the increasing use of LLMs in scientific papers
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