Fetching the paper…
Reading the bibliography…
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities in various tasks (e.g., long-context understanding), and many benchmarks have been proposed.
The proof and measurement of association between two things
Charles Spearman · 1987
Earlier work this paper cites.
A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives: complete edition
Lorin W Anderson and David R Krathwohl · 2001
Earlier work this paper cites.
Nltk: The natural language toolkit
Edward Loper and Steven Bird · 2002
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
Earlier work this paper cites.
Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie · 2005
Earlier work this paper cites.
Collective classification in network data
Prithviraj Sen, Galileo Namata, Mustafa Bilgic, Lise Getoor, Brian Galligher, and Tina Eliassi-Rad · 2008
Earlier work this paper cites.
The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al · 2009
Earlier work this paper cites.
Dbscan: Past, present and future
Kamran Khan, Saif Ur Rehman, Kamran Aziz, Simon Fong, and Sababady Sarasvady · 2014
Earlier work this paper cites.
A diversity-promoting objective function for neural conversation models
Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao, and Bill Dolan · 2015
Earlier work this paper cites.
Inductive representation learning on large graphs
Will Hamilton, Zhitao Ying, and Jure Leskovec · 2017
Earlier work this paper cites.
A discourse-aware attention model for abstractive summarization of long documents
Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, and Nazli Goharian · 2018
Earlier work this paper cites.
Wikihow: A large scale text summarization dataset
Mahnaz Koupaee and William Yang Wang · 2018
Earlier work this paper cites.
Text completion using context-integrated dependency parsing
Amr Rekaby Salama, Özge Alaçam, and Wolfgang Menzel · 2018
Earlier work this paper cites.
Multi-news: A large-scale multi-document summarization dataset and abstractive hierarchical model
Alexander Richard Fabbri, Irene Li, Tianwei She, Suyi Li, and Dragomir Radev · 2019
Earlier work this paper cites.
Eli5: Long form question answering
Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, and Michael Auli · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Earlier work this paper cites.
Long and diverse text generation with planning-based hierarchical variational model
Zhihong Shao, Minlie Huang, Jiangtao Wen, Wenfei Xu, and Xiaoyan Zhu · 2019
Earlier work this paper cites.
Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2020
Earlier work this paper cites.
Plan ahead: Self-supervised text planning for paragraph completion task
Dongyeop Kang and Eduard Hovy · 2020
Earlier work this paper cites.
Assessment of word-level neural language models for sentence completion
Heewoong Park and Jonghun Park · 2020
Earlier work this paper cites.
Automatic text summarization: A comprehensive survey
Wafaa S El-Kassas, Cherif R Salama, Ahmed A Rafea, and Hoda K Mohamed · 2021
Earlier work this paper cites.
Efficient attentions for long document summarization
Luyang Huang, Shuyang Cao, Nikolaus Parulian, Heng Ji, and Lu Wang · 2021
Earlier work this paper cites.
Phrase-bert: Improved phrase embeddings from bert with an application to corpus exploration
Shufan Wang, Laure Thompson, and Mohit Iyyer · 2021
Earlier work this paper cites.
Ethical and social risks of harm from language models
Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, et al · 2021
Earlier work this paper cites.
Qmsum: A new benchmark for query-based multi-domain meeting summarization
Ming Zhong, Da Yin, Tao Yu, Ahmad Zaidi, Mutethia Mutuma, Rahul Jha, Ahmed Hassan, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, et al · 2021
Earlier work this paper cites.
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
Earlier work this paper cites.
Asqa: Factoid questions meet long-form answers
Ivan Stelmakh, Yi Luan, Bhuwan Dhingra, and Ming-Wei Chang · 2022
Earlier work this paper cites.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Cited alongside, same era.
Longlora: Efficient fine-tuning of long-context large language models
Yukang Chen, Shengju Qian, Haotian Tang, Xin Lai, Zhijian Liu, Song Han, and Jiaya Jia · 2023
Cited alongside, same era.
Gptscore: Evaluate as you desire
Jinlan Fu, See-Kiong Ng, Zhengbao Jiang, and Pengfei Liu · 2023
Cited alongside, same era.
Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, et al · 2023
Cited alongside, same era.
Towards trustworthy ai: A review of ethical and robust large language models
Md Meftahul Ferdaus, Mahdi Abdelguerfi, Elias Ioup, Kendall N Niles, Ken Pathak, and Steven Sloan · 2024
Closest in time.
Longins: A challenging long-context instruction-based exam for llms
Shawn Gavin, Tuney Zheng, Jiaheng Liu, Quehry Que, Noah Wang, Jian Yang, Chenchen Zhang, Wenhao Huang, Wenhu Chen, and Ge Zhang · 2024
Closest in time.
Chatglm: A family of large language models from glm-130b to glm-4 all tools
Team GLM, Aohan Zeng, Bin Xu, Bowen Wang, Chenhui Zhang, Da Yin, Diego Rojas, Guanyu Feng, Hanlin Zhao, Hanyu Lai, et al · 2024
Closest in time.
Raw text is all you need: Knowledge-intensive multi-turn instruction tuning for large language model
Xia Hou, Qifeng Li, Jian Yang, Tongliang Li, Linzheng Chai, Xianjie Wu, Hangyuan Ji, Zhoujun Li, Jixuan Nie, Jingbo Dun, et al · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al · 2023
Cited alongside, same era.
Longform: Optimizing instruction tuning for long text generation with corpus extraction
Abdullatif Köksal, Timo Schick, Anna Korhonen, and Hinrich Schütze · 2023
Cited alongside, same era.
How long can context length of open-source llms truly promise?
Dacheng Li, Rulin Shao, Anze Xie, Ying Sheng, Lianmin Zheng, Joseph Gonzalez, Ion Stoica, Xuezhe Ma, and Hao Zhang · 2023
Cited alongside, same era.
Open-ended long text generation via masked language modeling
Xiaobo Liang, Zecheng Tang, Juntao Li, and Min Zhang · 2023
Cited alongside, same era.
Yen-Ting Lin and Yun-Nung Chen · 2023
Cited alongside, same era.
G-eval: Nlg evaluation using gpt-4 with better human alignment
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu · 2023
Cited alongside, same era.
# instag: Instruction tagging for analyzing supervised fine-tuning of large language models
Keming Lu, Hongyi Yuan, Zheng Yuan, Runji Lin, Junyang Lin, Chuanqi Tan, Chang Zhou, and Jingren Zhou · 2023
Cited alongside, same era.
Expertqa: Expert-curated questions and attributed answers
Chaitanya Malaviya, Subin Lee, Sihao Chen, Elizabeth Sieber, Mark Yatskar, and Dan Roth · 2023
Cited alongside, same era.
Hanlei Jin, Yang Zhang, Dan Meng, Jun Wang, and Jinghua Tan · 2024
Closest in time.
Checkeval: Robust evaluation framework using large language model via checklist
Yukyung Lee, Joonghoon Kim, Jaehee Kim, Hyowon Cho, and Pilsung Kang · 2024
Closest in time.
Long-context llms struggle with long in-context learning
Tianle Li, Ge Zhang, Quy Duc Do, Xiang Yue, and Wenhu Chen · 2024
Closest in time.
Wildbench: Benchmarking llms with challenging tasks from real users in the wild
Bill Yuchen Lin, Yuntian Deng, Khyathi Chandu, Faeze Brahman, Abhilasha Ravichander, Valentina Pyatkin, Nouha Dziri, Ronan Le Bras, and Yejin Choi · 2024
Closest in time.
Repoagent: An llm-powered open-source framework for repository-level code documentation generation
Qinyu Luo, Yining Ye, Shihao Liang, Zhong Zhang, Yujia Qin, Yaxi Lu, Yesai Wu, Xin Cong, Yankai Lin, Yingli Zhang, et al · 2024
Closest in time.
Meet llama 3.1, 2024
Meta · 2024
Closest in time.
Gpt-4o mini: advancing cost-efficient intelligence, 2024
OpenAI · 2024
Closest in time.
Check-eval: A checklist-based approach for evaluating text quality
Jayr Pereira and Roberto Lotufo · 2024
Closest in time.
Suri: Multi-constraint instruction following for long-form text generation
Chau Minh Pham, Simeng Sun, and Mohit Iyyer · 2024
Closest in time.
Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2024
Closest in time.
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al · 2024
Closest in time.
Jie Ruan, Wenqing Wang, and Xiaojun Wan · 2024
Closest in time.
A systematic survey of prompt engineering in large language models: Techniques and applications
Pranab Sahoo, Ayush Kumar Singh, Sriparna Saha, Vinija Jain, Samrat Mondal, and Aman Chadha · 2024
Closest in time.
The good, the bad, and the greedy: Evaluation of llms should not ignore non-determinism, 2024
Yifan Song, Guoyin Wang, Sujian Li, and Bill Yuchen Lin · 2024
Closest in time.
Haochen Tan, Zhijiang Guo, Zhan Shi, Lu Xu, Zhili Liu, Xiaoguang Li, Yasheng Wang, Lifeng Shang, Qun Liu, and Linqi Song · 2024
Closest in time.
Gemma 2: Improving open language models at a practical size
Gemma Team, Morgane Riviere, Shreya Pathak, Pier Giuseppe Sessa, Cassidy Hardin, Surya Bhupatiraju, Léonard Hussenot, Thomas Mesnard, Bobak Shahriari, Alexandre Ramé, et al · 2024
Closest in time.
Collabstory: Multi-llm collaborative story generation and authorship analysis
Saranya Venkatraman, Nafis Irtiza Tripto, and Dongwon Lee · 2024
Closest in time.
Creating suspenseful stories: Iterative planning with large language models
Kaige Xie and Mark Riedl · 2024
Closest in time.
Benchmarking benchmark leakage in large language models
Ruijie Xu, Zengzhi Wang, Run-Ze Fan, and Pengfei Liu · 2024
Closest in time.
An Yang, Baosong Yang, Binyuan Hui, Bo Zheng, Bowen Yu, Chang Zhou, Chengpeng Li, Chengyuan Li, Dayiheng Liu, Fei Huang, et al · 2024
Closest in time.
A survey on recent advances in llm-based multi-turn dialogue systems
Zihao Yi, Jiarui Ouyang, Yuwen Liu, Tianhao Liao, Zhe Xu, and Ying Shen · 2024
Closest in time.
Yi: Open foundation models by 01. ai
Alex Young, Bei Chen, Chao Li, Chengen Huang, Ge Zhang, Guanwei Zhang, Heng Li, Jiangcheng Zhu, Jianqun Chen, Jing Chang, et al · 2024
Closest in time.
Wildchat: 1m chatgpt interaction logs in the wild
Wenting Zhao, Xiang Ren, Jack Hessel, Claire Cardie, Yejin Choi, and Yuntian Deng · 2024
Closest in time.
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, et al · 2024
Closest in time.