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2020 – today
- 2024
[j1]Siwen Luo
, Hamish Ivison, Soyeon Caren Han, Josiah Poon:
Local Interpretations for Explainable Natural Language Processing: A Survey. ACM Comput. Surv. 56(9): 232:1-232:36 (2024)- [c7]Dirk Groeneveld, Iz Beltagy, Evan Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi:
OLMo: Accelerating the Science of Language Models. ACL (1) 2024: 15789-15809 - [c6]Rabeeh Karimi Mahabadi, Hamish Ivison, Jaesung Tae, James Henderson, Iz Beltagy, Matthew E. Peters, Arman Cohan:
TESS: Text-to-Text Self-Conditioned Simplex Diffusion. EACL (1) 2024: 2347-2361 - [c5]Yasaman Razeghi, Hamish Ivison, Sameer Singh, Yanai Elazar:
Backtracking Mathematical Reasoning of Language Models to the Pretraining Data. Tiny Papers @ ICLR 2024 - [i11]Dirk Groeneveld, Iz Beltagy, Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi:
OLMo: Accelerating the Science of Language Models. CoRR abs/2402.00838 (2024) - [i10]Hamish Ivison, Yizhong Wang, Jiacheng Liu, Zeqiu Wu, Valentina Pyatkin, Nathan Lambert, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi:
Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback. CoRR abs/2406.09279 (2024) - [i9]Sriyash Poddar, Yanming Wan, Hamish Ivison, Abhishek Gupta, Natasha Jaques:
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning. CoRR abs/2408.10075 (2024) - [i8]Nathan Lambert, Jacob Morrison, Valentina Pyatkin, Shengyi Huang, Hamish Ivison, Faeze Brahman, Lester James V. Miranda, Alisa Liu, Nouha Dziri, Shane Lyu, Yuling Gu, Saumya Malik, Victoria Graf, Jena D. Hwang, Jiangjiang Yang, Ronan Le Bras, Oyvind Tafjord, Chris Wilhelm, Luca Soldaini, Noah A. Smith, Yizhong Wang, Pradeep Dasigi, Hannaneh Hajishirzi:
TÜLU 3: Pushing Frontiers in Open Language Model Post-Training. CoRR abs/2411.15124 (2024) - 2023
- [c4]Hamish Ivison, Noah A. Smith, Hannaneh Hajishirzi, Pradeep Dasigi:
Data-Efficient Finetuning Using Cross-Task Nearest Neighbors. ACL (Findings) 2023: 9036-9061 - [c3]Hamish Ivison, Akshita Bhagia, Yizhong Wang, Hannaneh Hajishirzi, Matthew E. Peters:
HINT: Hypernetwork Instruction Tuning for Efficient Zero- and Few-Shot Generalisation. ACL (1) 2023: 11272-11288 - [c2]Yizhong Wang, Hamish Ivison, Pradeep Dasigi, Jack Hessel, Tushar Khot, Khyathi Raghavi Chandu, David Wadden, Kelsey MacMillan, Noah A. Smith, Iz Beltagy, Hannaneh Hajishirzi:
How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources. NeurIPS 2023 - [i7]Rabeeh Karimi Mahabadi, Jaesung Tae, Hamish Ivison, James Henderson, Iz Beltagy, Matthew E. Peters, Arman Cohan:
TESS: Text-to-Text Self-Conditioned Simplex Diffusion. CoRR abs/2305.08379 (2023) - [i6]Yizhong Wang, Hamish Ivison, Pradeep Dasigi, Jack Hessel, Tushar Khot, Khyathi Raghavi Chandu, David Wadden, Kelsey MacMillan, Noah A. Smith, Iz Beltagy, Hannaneh Hajishirzi:
How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources. CoRR abs/2306.04751 (2023) - [i5]Hamish Ivison, Yizhong Wang, Valentina Pyatkin, Nathan Lambert, Matthew E. Peters, Pradeep Dasigi, Joel Jang, David Wadden, Noah A. Smith, Iz Beltagy, Hannaneh Hajishirzi:
Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2. CoRR abs/2311.10702 (2023) - 2022
- [c1]Hamish Ivison, Matthew E. Peters:
Hyperdecoders: Instance-specific decoders for multi-task NLP. EMNLP (Findings) 2022: 1715-1730 - [i4]Hamish Ivison, Matthew E. Peters:
Hyperdecoders: Instance-specific decoders for multi-task NLP. CoRR abs/2203.08304 (2022) - [i3]Hamish Ivison, Noah A. Smith, Hannaneh Hajishirzi, Pradeep Dasigi:
Data-Efficient Finetuning Using Cross-Task Nearest Neighbors. CoRR abs/2212.00196 (2022) - [i2]Hamish Ivison, Akshita Bhagia, Yizhong Wang, Hannaneh Hajishirzi, Matthew E. Peters:
HINT: Hypernetwork Instruction Tuning for Efficient Zero-Shot Generalisation. CoRR abs/2212.10315 (2022) - 2021
- [i1]Siwen Luo, Hamish Ivison, Soyeon Caren Han, Josiah Poon:
Local Interpretations for Explainable Natural Language Processing: A Survey. CoRR abs/2103.11072 (2021)
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