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2020 – today
- 2024
[c20]David Wan, Koustuv Sinha, Srini Iyer, Asli Celikyilmaz, Mohit Bansal, Ramakanth Pasunuru:
ACUEval: Fine-grained Hallucination Evaluation and Correction for Abstractive Summarization. ACL (Findings) 2024: 10036-10056- [c19]Kumar Shridhar, Koustuv Sinha, Andrew Cohen, Tianlu Wang, Ping Yu, Ramakanth Pasunuru, Mrinmaya Sachan, Jason Weston, Asli Celikyilmaz:
The ART of LLM Refinement: Ask, Refine, and Trust. NAACL-HLT 2024: 5872-5883 - [i24]Silin Gao, Jane Dwivedi-Yu, Ping Yu, Xiaoqing Ellen Tan, Ramakanth Pasunuru, Olga Golovneva, Koustuv Sinha, Asli Celikyilmaz, Antoine Bosselut, Tianlu Wang:
Efficient Tool Use with Chain-of-Abstraction Reasoning. CoRR abs/2401.17464 (2024) - [i23]Han Lin, Tushar Nagarajan, Nicolas Ballas, Mido Assran, Mojtaba Komeili, Mohit Bansal, Koustuv Sinha:
VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning. CoRR abs/2410.03478 (2024) - 2023
- [j2]Dieuwke Hupkes, Mario Giulianelli
, Verna Dankers, Mikel Artetxe, Yanai Elazar, Tiago Pimentel, Christos E. Christodoulopoulos, Karim Lasri, Naomi Saphra, Arabella Sinclair, Dennis Ulmer, Florian Schottmann, Khuyagbaatar Batsuren, Kaiser Sun, Koustuv Sinha, Leila Khalatbari, Maria Ryskina, Rita Frieske, Ryan Cotterell, Zhijing Jin:
A taxonomy and review of generalization research in NLP. Nat. Mac. Intell. 5(10): 1161-1174 (2023) - [c18]Koustuv Sinha, Jon Gauthier, Aaron Mueller, Kanishka Misra, Keren Fuentes, Roger Levy, Adina Williams:
Language model acceptability judgements are not always robust to context. ACL (1) 2023: 6043-6063 - [c17]Saeed Goodarzi, Nikhil Kagita, Dennis Minn, Shufan Wang, Roberto Dessì, Shubham Toshniwal, Adina Williams, Jack Lanchantin, Koustuv Sinha:
Robustness of Named-Entity Replacements for In-Context Learning. EMNLP (Findings) 2023: 10914-10931 - [i22]Kumar Shridhar, Koustuv Sinha, Andrew Cohen, Tianlu Wang, Ping Yu, Ram Pasunuru, Mrinmaya Sachan, Jason Weston, Asli Celikyilmaz:
The ART of LLM Refinement: Ask, Refine, and Trust. CoRR abs/2311.07961 (2023) - 2022
- [c16]Ana Lucic, Maurits J. R. Bleeker, Samarth Bhargav, Jessica Zosa Forde, Koustuv Sinha, Jesse Dodge, Sasha Luccioni, Robert Stojnic:
Towards Reproducible Machine Learning Research in Natural Language Processing. ACL (tutorial) 2022: 7-11 - [c15]Itay Itzhak, Koustuv Sinha, Brenden M. Lake, Adina Williams, Dieuwke Hupkes:
Evaluating locality in NMT models. CogSci 2022 - [c14]Shanya Sharma, Manan Dey, Koustuv Sinha:
How sensitive are translation systems to extra contexts? Mitigating gender bias in Neural Machine Translation models through relevant contexts. EMNLP (Findings) 2022: 1968-1984 - [c13]Koustuv Sinha, Amirhossein Kazemnejad, Siva Reddy, Joelle Pineau, Dieuwke Hupkes, Adina Williams:
The Curious Case of Absolute Position Embeddings. EMNLP (Findings) 2022: 4449-4472 - [c12]Ana Lucic, Maurits J. R. Bleeker, Maarten de Rijke, Koustuv Sinha, Sami Jullien, Robert Stojnic:
Towards Reproducible Machine Learning Research in Information Retrieval. SIGIR 2022: 3459-3461 - [i21]Shanya Sharma, Manan Dey, Koustuv Sinha:
How sensitive are translation systems to extra contexts? Mitigating gender bias in Neural Machine Translation models through relevant contexts. CoRR abs/2205.10762 (2022) - [i20]Dieuwke Hupkes, Mario Giulianelli, Verna Dankers, Mikel Artetxe, Yanai Elazar, Tiago Pimentel, Christos Christodoulopoulos, Karim Lasri, Naomi Saphra, Arabella Sinclair, Dennis Ulmer, Florian Schottmann, Khuyagbaatar Batsuren, Kaiser Sun, Koustuv Sinha, Leila Khalatbari, Maria Ryskina, Rita Frieske, Ryan Cotterell, Zhijing Jin:
State-of-the-art generalisation research in NLP: a taxonomy and review. CoRR abs/2210.03050 (2022) - [i19]Koustuv Sinha, Amirhossein Kazemnejad, Siva Reddy, Joelle Pineau, Dieuwke Hupkes, Adina Williams:
The Curious Case of Absolute Position Embeddings. CoRR abs/2210.12574 (2022) - [i18]Koustuv Sinha, Jon Gauthier, Aaron Mueller, Kanishka Misra, Keren Fuentes, Roger Levy, Adina Williams:
Language model acceptability judgements are not always robust to context. CoRR abs/2212.08979 (2022) - 2021
- [j1]Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle:
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program). J. Mach. Learn. Res. 22: 164:1-164:20 (2021) - [c11]Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, Adina Williams:
UnNatural Language Inference. ACL/IJCNLP (1) 2021: 7329-7346 - [c10]Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, Douwe Kiela:
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little. EMNLP (1) 2021: 2888-2913 - [c9]Prasanna Parthasarathi, Koustuv Sinha, Joelle Pineau, Adina Williams:
Sometimes We Want Ungrammatical Translations. EMNLP (Findings) 2021: 3205-3227 - [i17]Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, Adina Williams:
Unnatural Language Inference. CoRR abs/2101.00010 (2021) - [i16]Anuroop Sriram, Matthew J. Muckley, Koustuv Sinha, Farah Shamout, Joelle Pineau, Krzysztof J. Geras, Lea Azour, Yindalon Aphinyanaphongs, Nafissa Yakubova, William Moore:
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction. CoRR abs/2101.04909 (2021) - [i15]Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, Douwe Kiela:
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little. CoRR abs/2104.06644 (2021) - [i14]Prasanna Parthasarathi, Koustuv Sinha, Joelle Pineau, Adina Williams:
Sometimes We Want Translationese. CoRR abs/2104.07623 (2021) - [i13]Shanya Sharma, Manan Dey, Koustuv Sinha:
Evaluating Gender Bias in Natural Language Inference. CoRR abs/2105.05541 (2021) - 2020
- [c8]Emily Goodwin, Koustuv Sinha, Timothy J. O'Donnell:
Probing Linguistic Systematicity. ACL 2020: 1958-1969 - [c7]Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, Joelle Pineau:
Learning an Unreferenced Metric for Online Dialogue Evaluation. ACL 2020: 2430-2441 - [c6]Nicolas Gontier, Koustuv Sinha, Siva Reddy, Christopher Pal:
Measuring Systematic Generalization in Neural Proof Generation with Transformers. NeurIPS 2020 - [i12]Koustuv Sinha, Shagun Sodhani, Joelle Pineau, William L. Hamilton:
Evaluating Logical Generalization in Graph Neural Networks. CoRR abs/2003.06560 (2020) - [i11]Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle:
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program). CoRR abs/2003.12206 (2020) - [i10]Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, Joelle Pineau:
Learning an Unreferenced Metric for Online Dialogue Evaluation. CoRR abs/2005.00583 (2020) - [i9]Emily Goodwin, Koustuv Sinha, Timothy J. O'Donnell:
Probing Linguistic Systematicity. CoRR abs/2005.04315 (2020) - [i8]Shagun Sodhani, Mayoore S. Jaiswal, Lauren Baker, Koustuv Sinha, Carl Shneider, Peter Henderson, Joel Lehman, Ryan Lowe:
Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop. CoRR abs/2007.10546 (2020) - [i7]Nicolas Gontier, Koustuv Sinha, Siva Reddy, Christopher Pal:
Measuring Systematic Generalization in Neural Proof Generation with Transformers. CoRR abs/2009.14786 (2020) - [i6]Shagun Sodhani, Olivier Delalleau, Mahmoud Assran, Koustuv Sinha, Nicolas Ballas, Michael G. Rabbat:
A Closer Look at Codistillation for Distributed Training. CoRR abs/2010.02838 (2020)
2010 – 2019
- 2019
- [c5]Emily Goodwin, Koustuv Sinha, Timothy J. O'Donnell:
Evaluating systematicity in neural networks with natural language inference. CogSci 2019: 3466 - [c4]Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, William L. Hamilton:
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text. EMNLP/IJCNLP (1) 2019: 4505-4514 - [i5]Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, William L. Hamilton:
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text. CoRR abs/1908.06177 (2019) - 2018
- [c3]Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau:
Ethical Challenges in Data-Driven Dialogue Systems. AIES 2018: 123-129 - [c2]Koustuv Sinha, Yue Dong, Jackie Chi Kit Cheung, Derek Ruths:
A Hierarchical Neural Attention-based Text Classifier. EMNLP 2018: 817-823 - [i4]Peter Henderson, Koustuv Sinha, Nan Rosemary Ke, Joelle Pineau:
Adversarial Gain. CoRR abs/1811.01302 (2018) - [i3]Nicolas Gontier, Koustuv Sinha, Peter Henderson, Iulian Serban, Michael Noseworthy, Prasanna Parthasarathi, Joelle Pineau:
The RLLChatbot: a solution to the ConvAI challenge. CoRR abs/1811.02714 (2018) - [i2]Koustuv Sinha, Shagun Sodhani, William L. Hamilton, Joelle Pineau:
Compositional Language Understanding with Text-based Relational Reasoning. CoRR abs/1811.02959 (2018) - 2017
- [c1]Andrew Piper, Mark Algee-Hewitt, Koustuv Sinha, Derek Ruths, Hardik Vala:
Studying Literary Characters and Character Networks. DH 2017 - [i1]Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau:
Ethical Challenges in Data-Driven Dialogue Systems. CoRR abs/1711.09050 (2017)
Coauthor Index
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