Amanda Bertsch

33 papers A* 4Journal 20Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Better Instruction-Following Through Minimum Bayes Risk. ICLR Ian Wu, Patrick Fernandes, Amanda Bertsch, Seungone Kim, Sina Khoshfetrat Pakazad, Graham Neubig
2025	—	`conf`	Efficient Many-Shot In-Context Learning with Dynamic Block-Sparse Attention. ACL (1) Emily Xiao, Chin-Jou Li, Yilin Zhang, Graham Neubig, Amanda Bertsch
2025	J	`jnl`	Efficient Many-Shot In-Context Learning with Dynamic Block-Sparse Attention. CoRR Emily Xiao, Chin-Jou Li, Yilin Zhang, Graham Neubig, Amanda Bertsch
2025	—	`conf`	FicSim: A Dataset for Multi-Faceted Semantic Similarity in Long-Form Fiction. EMNLP (Findings) Natasha Johnson, Amanda Bertsch, Maria-Emil Deal, Emma Strubell
2025	J	`jnl`	FicSim: A Dataset for Multi-Faceted Semantic Similarity in Long-Form Fiction. CoRR Natasha Johnson, Amanda Bertsch, Maria-Emil Deal, Emma Strubell
2025	—	`conf`	In-Context Learning with Long-Context Models: An In-Depth Exploration. NAACL (Long Papers) Amanda Bertsch, Maor Ivgi, Emily Xiao, Uri Alon, Jonathan Berant, Matthew R. Gormley, Graham Neubig
2025	—	`conf`	LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs. CHI Extended Abstracts Tongshuang Wu, Haiyi Zhu, Maya Albayrak, Alexis Axon, Amanda Bertsch, Wenxing Deng, Ziqi Ding, Boyuan Guo, Sireesh Gururaja, Tzu-Sheng Kuo, Jenny T. Liang, Ryan Liu, Ihita Mandal, Jeremiah Milbauer, Xiaolin Ni, Namrata Padmanabhan, Subhashini Ramkumar, Alexis Sudjianto, Jordan Taylor, Ying-Jui Tseng, Patricia Vaidos, Zhijin Wu, Wei Wu, Chenyang Yang
2025	A*	`conf`	Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions. EMNLP Emmy Liu, Amanda Bertsch, Lintang Sutawika, Lindia Tjuatja, Patrick Fernandes, Lara Marinov, Michael Chen, Shreya Singhal, Carolin Lawrence, Aditi Raghunathan, Kiril Gashteovski, Graham Neubig
2025	J	`jnl`	Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions. CoRR Emmy Liu, Amanda Bertsch, Lintang Sutawika, Lindia Tjuatja, Patrick Fernandes, Lara Marinov, Michael Chen, Shreya Singhal, Carolin Lawrence, Aditi Raghunathan, Kiril Gashteovski, Graham Neubig
2025	J	`jnl`	Olmo 3. CoRR Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, David Graham, David Heineman, Dirk Groeneveld, Faeze Brahman, Finbarr Timbers, Hamish Ivison, Jacob Morrison, Jake Poznanski, Kyle Lo, Luca Soldaini, Matt Jordan, Mayee F. Chen, Michael Noukhovitch, Nathan Lambert, Pete Walsh, Pradeep Dasigi, Robert Berry, Saumya Malik, Saurabh Shah, Scott Geng, Shane Arora, Shashank Gupta, Taira Anderson, Teng Xiao, Tyler Murray, Tyler Romero, Victoria Graf, Akari Asai, Akshita Bhagia, Alexander Wettig, Alisa Liu, Aman Rangapur, Chloe Anastasiades, Costa Huang, Dustin Schwenk, Harsh Trivedi, Ian Magnusson, Jaron Lochner, Jiacheng Liu, Lester James V. Miranda, Maarten Sap, Malia Morgan, Michael Schmitz, Michal Guerquin, Michael Wilson, Regan Huff, Ronan Le Bras, Rui Xin, Rulin Shao, Sam Skjonsberg, Shannon Zejiang Shen, Shuyue Stella Li, Tucker Wilde, Valentina Pyatkin, William Merrill, Yapei Chang, Yuling Gu, Zhiyuan Zeng, Ashish Sabharwal, Luke Zettlemoyer, Pang Wei Koh, Ali Farhadi, Noah A. Smith, Hannaneh Hajishirzi
2025	J	`jnl`	Oolong: Evaluating Long Context Reasoning and Aggregation Capabilities. CoRR Amanda Bertsch, Adithya Pratapa, Teruko Mitamura, Graham Neubig, Matthew R. Gormley
2025	J	`jnl`	Prompt-MII: Meta-Learning Instruction Induction for LLMs. CoRR Emily Xiao, Yixiao Zeng, Ada Chen, Chin-Jou Li, Amanda Bertsch, Graham Neubig
2024	—	`conf`	A Taxonomy for Data Contamination in Large Language Models. CONDA Medha Palavalli, Amanda Bertsch, Matthew Gormley
2024	J	`jnl`	A Taxonomy for Data Contamination in Large Language Models. CoRR Medha Palavalli, Amanda Bertsch, Matthew R. Gormley
2024	J	`jnl`	Better Instruction-Following Through Minimum Bayes Risk. CoRR Ian Wu, Patrick Fernandes, Amanda Bertsch, Seungone Kim, Sina Pakazad, Graham Neubig
2024	J	`jnl`	From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models. CoRR Sean Welleck, Amanda Bertsch, Matthew Finlayson, Hailey Schoelkopf, Alex Xie, Graham Neubig, Ilia Kulikov, Zaïd Harchaoui
2024	J	`jnl`	From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models. Trans. Mach. Learn. Res. Sean Welleck, Amanda Bertsch, Matthew Finlayson, Hailey Schoelkopf, Alex Xie, Graham Neubig, Ilia Kulikov, Zaïd Harchaoui
2024	J	`jnl`	In-Context Learning with Long-Context Models: An In-Depth Exploration. CoRR Amanda Bertsch, Maor Ivgi, Uri Alon, Jonathan Berant, Matthew R. Gormley, Graham Neubig
2023	J	`jnl`	Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation. CoRR Patrick Fernandes, Aman Madaan, Emmy Liu, António Farinhas, Pedro Henrique Martins, Amanda Bertsch, José G. C. de Souza, Shuyan Zhou, Tongshuang Wu, Graham Neubig, André F. T. Martins
2023	J	`jnl`	Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation. Trans. Assoc. Comput. Linguistics Patrick Fernandes, Aman Madaan, Emmy Liu, António Farinhas, Pedro Henrique Martins, Amanda Bertsch, José G. C. de Souza, Shuyan Zhou, Tongshuang Wu, Graham Neubig, André F. T. Martins
2023	J	`jnl`	It's MBR All the Way Down: Modern Generation Techniques Through the Lens of Minimum Bayes Risk. CoRR Amanda Bertsch, Alex Xie, Graham Neubig, Matthew R. Gormley
2023	J	`jnl`	LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs. CoRR Tongshuang Wu, Haiyi Zhu, Maya Albayrak, Alexis Axon, Amanda Bertsch, Wenxing Deng, Ziqi Ding, Bill Guo, Sireesh Gururaja, Tzu-Sheng Kuo, Jenny T. Liang, Ryan Liu, Ihita Mandal, Jeremiah Milbauer, Xiaolin Ni, Namrata Padmanabhan, Subhashini Ramkumar, Alexis Sudjianto, Jordan Taylor, Ying-Jui Tseng, Patricia Vaidos, Zhijin Wu, Wei Wu, Chenyang Yang
2023	—	`conf`	Prompt2Model: Generating Deployable Models from Natural Language Instructions. EMNLP (Demos) Vijay Viswanathan, Chenyang Zhao, Amanda Bertsch, Tongshuang Wu, Graham Neubig
2023	J	`jnl`	Prompt2Model: Generating Deployable Models from Natural Language Instructions. CoRR Vijay Viswanathan, Chenyang Zhao, Amanda Bertsch, Tongshuang Wu, Graham Neubig
2023	—	`conf`	SummQA at MEDIQA-Chat 2023: In-Context Learning with GPT-4 for Medical Summarization. ClinicalNLP@ACL Yash Mathur, Sanketh Rangreji, Raghav Kapoor, Medha Palavalli, Amanda Bertsch, Matthew Gormley
2023	J	`jnl`	SummQA at MEDIQA-Chat 2023: In-Context Learning with GPT-4 for Medical Summarization. CoRR Yash Mathur, Sanketh Rangreji, Raghav Kapoor, Medha Palavalli, Amanda Bertsch, Matthew R. Gormley
2023	A*	`conf`	To Build Our Future, We Must Know Our Past: Contextualizing Paradigm Shifts in Natural Language Processing. EMNLP Sireesh Gururaja, Amanda Bertsch, Clara Na, David Gray Widder, Emma Strubell
2023	J	`jnl`	To Build Our Future, We Must Know Our Past: Contextualizing Paradigm Shifts in Natural Language Processing. CoRR Sireesh Gururaja, Amanda Bertsch, Clara Na, David Gray Widder, Emma Strubell
2023	A*	`conf`	Unlimiformer: Long-Range Transformers with Unlimited Length Input. NeurIPS Amanda Bertsch, Uri Alon, Graham Neubig, Matthew Gormley
2023	J	`jnl`	Unlimiformer: Long-Range Transformers with Unlimited Length Input. CoRR Amanda Bertsch, Uri Alon, Graham Neubig, Matthew R. Gormley
2022	—	`conf`	He Said, She Said: Style Transfer for Shifting the Perspective of Dialogues. EMNLP (Findings) Amanda Bertsch, Graham Neubig, Matthew R. Gormley
2022	J	`jnl`	He Said, She Said: Style Transfer for Shifting the Perspective of Dialogues. CoRR Amanda Bertsch, Graham Neubig, Matthew R. Gormley
2021	—	`conf`	Detection of Puffery on the English Wikipedia. W-NUT Amanda Bertsch, Steven Bethard