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2020 – today
- 2024
[c9]Satwik Bhattamishra, Arkil Patel, Phil Blunsom, Varun Kanade:
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions. ICLR 2024- [c8]Arkil Patel, Siva Reddy, Dzmitry Bahdanau, Pradeep Dasigi:
Evaluating In-Context Learning of Libraries for Code Generation. NAACL-HLT 2024: 2908-2926 - [i9]Nicholas Meade, Arkil Patel, Siva Reddy:
Universal Adversarial Triggers Are Not Universal. CoRR abs/2404.16020 (2024) - 2023
- [c7]Satwik Bhattamishra, Arkil Patel, Varun Kanade, Phil Blunsom:
Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions. ACL (1) 2023: 5767-5791 - [c6]Arkil Patel, Satwik Bhattamishra, Siva Reddy, Dzmitry Bahdanau:
MAGNIFICo: Evaluating the In-Context Learning Ability of Large Language Models to Generalize to Novel Interpretations. EMNLP 2023: 2167-2189 - [i8]Satwik Bhattamishra, Arkil Patel, Phil Blunsom, Varun Kanade:
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions. CoRR abs/2310.03016 (2023) - [i7]Arkil Patel, Satwik Bhattamishra, Siva Reddy, Dzmitry Bahdanau:
MAGNIFICo: Evaluating the In-Context Learning Ability of Large Language Models to Generalize to Novel Interpretations. CoRR abs/2310.11634 (2023) - [i6]Arkil Patel, Siva Reddy, Dzmitry Bahdanau, Pradeep Dasigi:
Evaluating In-Context Learning of Libraries for Code Generation. CoRR abs/2311.09635 (2023) - 2022
- [c5]Arkil Patel, Satwik Bhattamishra, Phil Blunsom, Navin Goyal:
Revisiting the Compositional Generalization Abilities of Neural Sequence Models. ACL (2) 2022: 424-434 - [c4]Ankur Sikarwar
, Arkil Patel, Navin Goyal:
When Can Transformers Ground and Compose: Insights from Compositional Generalization Benchmarks. EMNLP 2022: 648-669 - [i5]Arkil Patel, Satwik Bhattamishra, Phil Blunsom, Navin Goyal:
Revisiting the Compositional Generalization Abilities of Neural Sequence Models. CoRR abs/2203.07402 (2022) - [i4]Ankur Sikarwar, Arkil Patel, Navin Goyal:
When Can Transformers Ground and Compose: Insights from Compositional Generalization Benchmarks. CoRR abs/2210.12786 (2022) - [i3]Satwik Bhattamishra, Arkil Patel, Varun Kanade, Phil Blunsom:
Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions. CoRR abs/2211.12316 (2022) - 2021
- [c3]Arkil Patel, Satwik Bhattamishra, Navin Goyal:
Are NLP Models really able to Solve Simple Math Word Problems? NAACL-HLT 2021: 2080-2094 - [i2]Arkil Patel, Satwik Bhattamishra, Navin Goyal:
Are NLP Models really able to Solve Simple Math Word Problems? CoRR abs/2103.07191 (2021) - 2020
- [c2]Satwik Bhattamishra, Arkil Patel, Navin Goyal:
On the Computational Power of Transformers and Its Implications in Sequence Modeling. CoNLL 2020: 455-475 - [i1]Satwik Bhattamishra, Arkil Patel, Navin Goyal:
On the Computational Power of Transformers and Its Implications in Sequence Modeling. CoRR abs/2006.09286 (2020)
2010 – 2019
- 2019
- [c1]Arkil Patel, Naigam Shah, Trupil Limbasiya, Debasis Das:
VehicleChain: Blockchain-based Vehicular Data Transmission Scheme for Smart City. SMC 2019: 661-667
Coauthor Index
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last updated on 2024-08-30 21:37 CEST by the dblp team
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