Fetching the paper…
Reading the bibliography…
Large Language Models (LLMs) have revolutionized various domains with extensive knowledge and creative capabilities.
Learning phrase representations using RNN encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Facenet: A unified embedding for face recognition and clustering
Florian Schroff, Dmitry Kalenichenko, and James Philbin. 2015b · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
Earlier work this paper cites.
Axiomatic attribution for deep networks
Mukund Sundararajan, Ankur Taly, and Qiqi Yan. 2017 · 2017
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Earlier work this paper cites.
Generalized out-of-distribution detection: A survey
Jingkang Yang, Kaiyang Zhou, Yixuan Li, and Ziwei Liu. 2021 · 2021
Earlier work this paper cites.
Transformer feed-forward layers build predictions by promoting concepts in the vocabulary space
Mor Geva, Avi Caciularu, Kevin Wang, and Yoav Goldberg. 2022 · 2022
Earlier work this paper cites.
Locating and editing factual associations in GPT
Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov. 2022 · 2022
Earlier work this paper cites.
Llm based generation of item-description for recommendation system
Arkadeep Acharya, Brijraj Singh, and Naoyuki Onoe. 2023 · 2023
Earlier work this paper cites.
The internal state of an llm knows when its lying
Amos Azaria and Tom Mitchell. 2023 · 2023
Earlier work this paper cites.
Discovering latent knowledge in language models without supervision
Collin Burns, Haotian Ye, Dan Klein, and Jacob Steinhardt. 2023 · 2023
Earlier work this paper cites.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023
Earlier work this paper cites.
Chatlaw: Open-source legal large language model with integrated external knowledge bases
Jiaxi Cui, Zongjian Li, Yang Yan, Bohua Chen, and Li Yuan. 2023 · 2023
Earlier work this paper cites.
Billionaires statistics dataset
Nidula Elgiriyewithana. 2023 · 2023
Earlier work this paper cites.
Nobel laureates dataset
The Nobel Foundation. 2023 · 2023
Cited alongside, same era.
Movies dataset
Daniel Grijalvas. 2023 · 2023
Cited alongside, same era.
Olympic games dataset
The Guardian. 2023 · 2023
Cited alongside, same era.
Overthinking the truth: Understanding how language models process false demonstrations
Danny Halawi, Jean-Stanislas Denain, and Jacob Steinhardt. 2023 · 2023
Cited alongside, same era.
Good-looking but lacking faithfulness: Understanding local explanation methods through trend-based testing
Jinwen He, Kai Chen, Guozhu Meng, Jiangshan Zhang, and Congyi Li. 2023 · 2023
Cited alongside, same era.
Natural language processing: State of the art, current trends and challenges
Diksha Khurana, Aditya Koli, Kiran Khatter, and Sukhdev Singh. 2023 · 2023
Distinguishing fact from fiction: A benchmark dataset for identifying machine-generated scientific papers in the LLM era
Edoardo Mosca, Mohamed Hesham Ibrahim Abdalla, Paolo Basso, Margherita Musumeci, and Georg Groh. 2023 · 2023
Closest in time.
Goodreads best books dataset
Naren. 2023 · 2023
Closest in time.
Guilherme Penedo, Quentin Malartic, Daniel Hesslow, Ruxandra-Aimée Cojocaru, Alessandro Cappelli, Hamza Alobeidli, Baptiste Pannier, Ebtesam Almazrouei, and Julien Launay. 2023 · 2023
Closest in time.
Investigating the factual knowledge boundary of large language models with retrieval augmentation
Ruiyang Ren, Yuhao Wang, Yingqi Qu, Wayne Xin Zhao, J. Liu, Hao Tian, Huaqin Wu, Ji rong Wen, and Haifeng Wang. 2023 · 2023
Closest in time.
Kaggle: Your home for data science
D. Sculley. 2023 · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Semantic uncertainty: Linguistic invariances for uncertainty estimation in natural language generation
Lorenz Kuhn, Yarin Gal, and Sebastian Farquhar. 2023 · 2023
Cited alongside, same era.
Inference-time intervention: Eliciting truthful answers from a language model
Kenneth Li, Oam Patel, Fernanda Viégas, Hanspeter Pfister, and Martin Wattenberg. 2023 · 2023
Cited alongside, same era.
SelfCheckGPT: Zero-resource black-box hallucination detection for generative large language models
Potsawee Manakul, Adian Liusie, and Mark Gales. 2023 · 2023
Cited alongside, same era.
Samuel Marks and Max Tegmark. 2023 · 2023
Cited alongside, same era.
The hydra effect: Emergent self-repair in language model computations
Thomas McGrath, Matthew Rahtz, Janos Kramar, Vladimir Mikulik, and Shane Legg. 2023 · 2023
Cited alongside, same era.
Mass-editing memory in a transformer
Kevin Meng, Arnab Sen Sharma, Alex J. Andonian, Yonatan Belinkov, and David Bau. 2023 · 2023
Cited alongside, same era.
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
Closest in time.
Just ask for calibration: Strategies for eliciting calibrated confidence scores from language models fine-tuned with human feedback
Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, and Christopher Manning. 2023 · 2023
Closest in time.
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, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023
Closest in time.
The top paying sports teams and top paid athletes dataset
Prashant Upadhyay. 2023 · 2023
Closest in time.
Improving mathematics tutoring with a code scratchpad
Shriyash Upadhyay, Etan Ginsberg, and Chris Callison-Burch. 2023 · 2023
Closest in time.
Wikidata query service
Wikidata. 2023 · 2023
Closest in time.
INSIDE: LLMs’ internal states retain the power of hallucination detection
Chao Chen, Kai Liu, Ze Chen, Yi Gu, Yue Wu, Mingyuan Tao, Zhihang Fu, and Jieping Ye. 2024 · 2024
Closest in time.
Interpreting GPT: The logit lens
Nostalgebraist. 2020 · 2024
Closest in time.