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Conference and Workshop Papers
- 2024
[c32]Anthony Sicilia, Hyunwoo Kim, Khyathi Raghavi Chandu, Malihe Alikhani, Jack Hessel:
Deal, or no deal (or who knows)? Forecasting Uncertainty in Conversations using Large Language Models. ACL (Findings) 2024: 11700-11726- [c31]Da Yin, Faeze Brahman, Abhilasha Ravichander, Khyathi Raghavi Chandu, Kai-Wei Chang, Yejin Choi, Bill Yuchen Lin:
Agent Lumos: Unified and Modular Training for Open-Source Language Agents. ACL (1) 2024: 12380-12403 - [c30]Tejas Srinivasan, Jack Hessel, Tanmay Gupta, Bill Yuchen Lin, Yejin Choi, Jesse Thomason, Khyathi Raghavi Chandu:
Selective "Selective Prediction": Reducing Unnecessary Abstention in Vision-Language Reasoning. ACL (Findings) 2024: 12935-12948 - [c29]Luca Soldaini, Rodney Kinney, Akshita Bhagia, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi Raghavi Chandu, Jennifer Dumas, Yanai Elazar, Valentin Hofmann, Ananya Harsh Jha, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Evan Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, Kyle Lo:
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. ACL (1) 2024: 15725-15788 - [c28]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 - [c27]Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Raghavi Chandu, Chandra Bhagavatula, Yejin Choi:
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning. ICLR 2024 - [c26]Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Raghavi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi:
The Generative AI Paradox: "What It Can Create, It May Not Understand". ICLR 2024 - [c25]Marcel Nawrath, Agnieszka Nowak, Tristan Ratz, Danilo C. Walenta, Juri Opitz, Leonardo F. R. Ribeiro, João Sedoc, Daniel Deutsch, Simon Mille, Yixin Liu, Sebastian Gehrmann, Lining Zhang, Saad Mahamood, Miruna Clinciu, Khyathi Raghavi Chandu, Yufang Hou:
On the Role of Summary Content Units in Text Summarization Evaluation. NAACL (Short Papers) 2024: 272-281 - 2023
- [c24]Lining Zhang, Simon Mille, Yufang Hou, Daniel Deutsch, Elizabeth Clark, Yixin Liu, Saad Mahamood, Sebastian Gehrmann, Miruna Clinciu, Khyathi Raghavi Chandu, João Sedoc
:
A Needle in a Haystack: An Analysis of High-Agreement Workers on MTurk for Summarization. ACL (1) 2023: 14944-14982 - [c23]Peter West, Ronan Le Bras, Taylor Sorensen, Bill Yuchen Lin, Liwei Jiang, Ximing Lu, Khyathi Raghavi Chandu, Jack Hessel, Ashutosh Baheti, Chandra Bhagavatula, Yejin Choi:
NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation. EMNLP (Findings) 2023: 1127-1149 - [c22]Hyundong Cho, Andrea Madotto, Zhaojiang Lin, Khyathi Raghavi Chandu, Satwik Kottur, Jing Xu, Jonathan May, Chinnadhurai Sankar:
Continual Dialogue State Tracking via Example-Guided Question Answering. EMNLP 2023: 3873-3886 - [c21]Ximing Lu, Faeze Brahman, Peter West, Jaehun Jung, Khyathi Raghavi Chandu, Abhilasha Ravichander, Prithviraj Ammanabrolu, Liwei Jiang, Sahana Ramnath, Nouha Dziri, Jillian Fisher, Bill Y. Lin, Skyler Hallinan, Lianhui Qin, Xiang Ren, Sean Welleck, Yejin Choi:
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. EMNLP 2023: 6863-6883 - [c20]Khyathi Raghavi Chandu, David M. Howcroft, Dimitra Gkatzia, Yi-Ling Chung, Yufang Hou, Chris Chinenye Emezue, Pawan Rajpoot, Tosin P. Adewumi:
LOWRECORP: the Low-Resource NLG Corpus Building Challenge. INLG (Generation Challenges) 2023: 1-9 - [c19]Jae Sung Park, Jack Hessel, Khyathi Raghavi Chandu, Paul Pu Liang, Ximing Lu, Peter West, Youngjae Yu, Qiuyuan Huang, Jianfeng Gao, Ali Farhadi, Yejin Choi:
Localized Symbolic Knowledge Distillation for Visual Commonsense Models. NeurIPS 2023 - [c18]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 - 2022
- [c17]Khyathi Raghavi Chandu, Piyush Sharma, Soravit Changpinyo, Ashish V. Thapliyal, Radu Soricut:
Denoising Large-Scale Image Captioning from Alt-text Data Using Content Selection Models. COLING 2022: 6089-6104 - 2021
- [c16]Khyathi Raghavi Chandu, Yonatan Bisk, Alan W. Black:
Grounding 'Grounding' in NLP. ACL/IJCNLP (Findings) 2021: 4283-4305 - [c15]Sai Muralidhar Jayanthi, Kavya Nerella, Khyathi Raghavi Chandu, Alan W. Black:
CodemixedNLP: An Extensible and Open NLP Toolkit for Code-Mixing. CALCS@NAACL 2021: 113-118 - [c14]Parul Chopra, Sai Krishna Rallabandi, Alan W. Black, Khyathi Raghavi Chandu:
Switch Point biased Self-Training: Re-purposing Pretrained Models for Code-Switching. EMNLP (Findings) 2021: 4389-4397 - 2020
- [c13]Khyathi Raghavi Chandu, Ruo-Ping Dong, Alan W. Black:
Reading Between the Lines: Exploring Infilling in Visual Narratives. EMNLP (1) 2020: 1220-1229 - [c12]Khyathi Raghavi Chandu, Alan W. Black:
Style Variation as a Vantage Point for Code-Switching. INTERSPEECH 2020: 4761-4765 - 2019
- [c11]Khyathi Raghavi Chandu, Eric Nyberg, Alan W. Black:
Storyboarding of Recipes: Grounded Contextual Generation. ACL (1) 2019: 6040-6046 - [c10]Khyathi Raghavi Chandu, Eric Nyberg, Alan W. Black:
Storyboarding of Recipes: Grounded Contextual Generation. DGS@ICLR 2019 - 2018
- [c9]Soumya Wadhwa, Khyathi Raghavi Chandu, Eric Nyberg:
Comparative Analysis of Neural QA models on SQuAD. QA@ACL 2018: 89-97 - [c8]Khyathi Raghavi Chandu, Ekaterina Loginova, Vishal Gupta, Josef van Genabith, Günter Neumann, Manoj Kumar Chinnakotla, Eric Nyberg, Alan W. Black:
Code-Mixed Question Answering Challenge: Crowd-sourcing Data and Techniques. CodeSwitch@ACL 2018: 29-38 - [c7]Khyathi Raghavi Chandu, Thomas Manzini, Sumeet Singh, Alan W. Black:
Language Informed Modeling of Code-Switched Text. CodeSwitch@ACL 2018: 92-97 - [c6]Parvathy Geetha, Khyathi Raghavi Chandu, Alan W. Black:
Tackling Code-Switched NER: Participation of CMU. CodeSwitch@ACL 2018: 126-131 - 2017
- [c5]Khyathi Raghavi Chandu, Aakanksha Naik, Aditya Chandrasekar, Zi Yang, Niloy Gupta, Eric Nyberg:
Tackling Biomedical Text Summarization: OAQA at BioASQ 5B. BioNLP 2017: 58-66 - [c4]Khyathi Raghavi Chandu, Manoj Kumar Chinnakotla, Alan W. Black, Manish Shrivastava:
WebShodh: A Code Mixed Factoid Question Answering System for Web. CLEF 2017: 104-111 - [c3]Divya Sai Jitta, Khyathi Raghavi Chandu, Harsha Pamidipalli, Radhika Mamidi:
"nee intention enti?" towards dialog act recognition in code-mixed conversations. IALP 2017: 243-246 - [c2]Khyathi Raghavi Chandu, Sai Krishna Rallabandi, Sunayana Sitaram, Alan W. Black:
Speech Synthesis for Mixed-Language Navigation Instructions. INTERSPEECH 2017: 57-61 - 2015
- [c1]Khyathi Chandu Raghavi, Manoj Kumar Chinnakotla, Manish Shrivastava:
"Answer ka type kya he?": Learning to Classify Questions in Code-Mixed Language. WWW (Companion Volume) 2015: 853-858
Informal and Other Publications
- 2024
- [i38]Luca Soldaini, Rodney Kinney, Akshita Bhagia, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi Raghavi Chandu, Jennifer Dumas, Yanai Elazar, Valentin Hofmann, Ananya Harsh Jha, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, Kyle Lo:
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. CoRR abs/2402.00159 (2024) - [i37]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) - [i36]Anthony Sicilia, Hyunwoo Kim, Khyathi Raghavi Chandu, Malihe Alikhani, Jack Hessel:
Deal, or no deal (or who knows)? Forecasting Uncertainty in Conversations using Large Language Models. CoRR abs/2402.03284 (2024) - [i35]Yutaro Yamada, Khyathi Raghavi Chandu, Bill Yuchen Lin, Jack Hessel, Ilker Yildirim, Yejin Choi:
L3GO: Language Agents with Chain-of-3D-Thoughts for Generating Unconventional Objects. CoRR abs/2402.09052 (2024) - [i34]Tejas Srinivasan, Jack Hessel, Tanmay Gupta, Bill Yuchen Lin, Yejin Choi, Jesse Thomason, Khyathi Raghavi Chandu:
Selective "Selective Prediction": Reducing Unnecessary Abstention in Vision-Language Reasoning. CoRR abs/2402.15610 (2024) - [i33]Nathan Lambert, Valentina Pyatkin, Jacob Morrison, LJ Miranda, Bill Yuchen Lin, Khyathi Raghavi Chandu, Nouha Dziri, Sachin Kumar, Tom Zick, Yejin Choi, Noah A. Smith, Hannaneh Hajishirzi:
RewardBench: Evaluating Reward Models for Language Modeling. CoRR abs/2403.13787 (2024) - [i32]Marcel Nawrath, Agnieszka Nowak, Tristan Ratz, Danilo C. Walenta, Juri Opitz, Leonardo F. R. Ribeiro, João Sedoc, Daniel Deutsch, Simon Mille, Yixin Liu, Lining Zhang, Sebastian Gehrmann, Saad Mahamood, Miruna Clinciu, Khyathi Raghavi Chandu, Yufang Hou:
On the Role of Summary Content Units in Text Summarization Evaluation. CoRR abs/2404.01701 (2024) - [i31]Bill Yuchen Lin, Yuntian Deng, Khyathi Raghavi Chandu, Faeze Brahman, Abhilasha Ravichander, Valentina Pyatkin, Nouha Dziri, Ronan Le Bras, Yejin Choi:
WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild. CoRR abs/2406.04770 (2024) - [i30]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. CoRR abs/2406.11794 (2024) - [i29]Khyathi Raghavi Chandu, Linjie Li, Anas Awadalla, Ximing Lu, Jae Sung Park, Jack Hessel, Lijuan Wang, Yejin Choi:
Certainly Uncertain: A Benchmark and Metric for Multimodal Epistemic and Aleatoric Awareness. CoRR abs/2407.01942 (2024) - [i28]Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, Pradeep Dasigi, Valentina Pyatkin, Abhilasha Ravichander, Sarah Wiegreffe, Nouha Dziri, Khyathi Raghavi Chandu, Jack Hessel, Yulia Tsvetkov, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi:
The Art of Saying No: Contextual Noncompliance in Language Models. CoRR abs/2407.12043 (2024) - [i27]Wenting Zhao, Tanya Goyal, Yu Ying Chiu, Liwei Jiang, Benjamin Newman, Abhilasha Ravichander, Khyathi Raghavi Chandu, Ronan Le Bras, Claire Cardie, Yuntian Deng, Yejin Choi:
WildHallucinations: Evaluating Long-form Factuality in LLMs with Real-World Entity Queries. CoRR abs/2407.17468 (2024) - 2023
- [i26]Khyathi Raghavi Chandu, Alborz Geramifard:
Curriculum Script Distillation for Multilingual Visual Question Answering. CoRR abs/2301.07227 (2023) - [i25]Hyundong Cho, Andrea Madotto, Zhaojiang Lin, Khyathi Raghavi Chandu, Satwik Kottur, Jing Xu, Jonathan May, Chinnadhurai Sankar:
Continual Dialogue State Tracking via Example-Guided Question Answering. CoRR abs/2305.13721 (2023) - [i24]Ximing Lu, Faeze Brahman, Peter West, Jaehun Jung, Khyathi Raghavi Chandu, Abhilasha Ravichander, Lianhui Qin, Prithviraj Ammanabrolu, Liwei Jiang, Sahana Ramnath, Nouha Dziri, Jillian Fisher, Bill Yuchen Lin, Skyler Hallinan, Xiang Ren, Sean Welleck, Yejin Choi:
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. CoRR abs/2305.15065 (2023) - [i23]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) - [i22]Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Raghavi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi:
The Generative AI Paradox: "What It Can Create, It May Not Understand". CoRR abs/2311.00059 (2023) - [i21]Da Yin, Faeze Brahman, Abhilasha Ravichander, Khyathi Raghavi Chandu, Kai-Wei Chang, Yejin Choi, Bill Yuchen Lin:
Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs. CoRR abs/2311.05657 (2023) - [i20]Yanai Elazar, Bhargavi Paranjape, Hao Peng, Sarah Wiegreffe, Khyathi Chandu Raghavi, Vivek Srikumar, Sameer Singh, Noah A. Smith:
Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals. CoRR abs/2311.09605 (2023) - [i19]Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Raghavi Chandu, Chandra Bhagavatula, Yejin Choi:
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning. CoRR abs/2312.01552 (2023) - [i18]Jae Sung Park, Jack Hessel, Khyathi Raghavi Chandu, Paul Pu Liang, Ximing Lu, Peter West, Youngjae Yu, Qiuyuan Huang, Jianfeng Gao, Ali Farhadi, Yejin Choi:
Localized Symbolic Knowledge Distillation for Visual Commonsense Models. CoRR abs/2312.04837 (2023) - [i17]Peter West, Ronan Le Bras, Taylor Sorensen, Bill Yuchen Lin, Liwei Jiang, Ximing Lu, Khyathi Raghavi Chandu, Jack Hessel, Ashutosh Baheti, Chandra Bhagavatula, Yejin Choi:
NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation. CoRR abs/2312.05979 (2023) - 2022
- [i16]Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran, Alex Wang, Alexandros Papangelis, Aman Madaan, Angelina McMillan-Major, Anna Shvets, Ashish Upadhyay, Bingsheng Yao, Bryan Wilie, Chandra Bhagavatula, Chaobin You, Craig Thomson, Cristina Garbacea, Dakuo Wang, Daniel Deutsch, Deyi Xiong, Di Jin, Dimitra Gkatzia, Dragomir R. Radev, Elizabeth Clark, Esin Durmus, Faisal Ladhak, Filip Ginter, Genta Indra Winata, Hendrik Strobelt, Hiroaki Hayashi, Jekaterina Novikova, Jenna Kanerva, Jenny Chim, Jiawei Zhou, Jordan Clive, Joshua Maynez, João Sedoc, Juraj Juraska, Kaustubh D. Dhole, Khyathi Raghavi Chandu, Laura Perez-Beltrachini, Leonardo F. R. Ribeiro, Lewis Tunstall, Li Zhang, Mahima Pushkarna, Mathias Creutz, Michael White, Mihir Sanjay Kale, Moussa Kamal Eddine, Nico Daheim, Nishant Subramani, Ondrej Dusek, Paul Pu Liang, Pawan Sasanka Ammanamanchi, Qi Zhu, Ratish Puduppully, Reno Kriz, Rifat Shahriyar, Ronald Cardenas, Saad Mahamood, Salomey Osei, Samuel Cahyawijaya, Sanja Stajner, Sébastien Montella, Shailza Jolly, Simon Mille, Tahmid Hasan, Tianhao Shen, Tosin P. AMahidewumi, Vikas Raunak, Vipul Raheja, Vitaly Nikolaev, Vivian Tsai, Yacine Jernite, Ying Xu, Yisi Sang, Yixin Liu, Yufang Hou:
GEMv2: Multilingual NLG Benchmarking in a Single Line of Code. CoRR abs/2206.11249 (2022) - [i15]Khyathi Raghavi Chandu, Alborz Geramifard:
Multilingual Multimodality: A Taxonomical Survey of Datasets, Techniques, Challenges and Opportunities. CoRR abs/2210.16960 (2022) - [i14]Lining Zhang, João Sedoc, Simon Mille, Yufang Hou, Sebastian Gehrmann, Daniel Deutsch, Elizabeth Clark, Yixin Liu, Miruna Clinciu, Saad Mahamood, Khyathi Raghavi Chandu:
Needle in a Haystack: An Analysis of Finding Qualified Workers on MTurk for Summarization. CoRR abs/2212.10397 (2022) - 2021
- [i13]Sebastian Gehrmann, Tosin P. Adewumi, Karmanya Aggarwal, Pawan Sasanka Ammanamanchi, Aremu Anuoluwapo, Antoine Bosselut, Khyathi Raghavi Chandu, Miruna-Adriana Clinciu, Dipanjan Das, Kaustubh D. Dhole, Wanyu Du, Esin Durmus, Ondrej Dusek, Chris Emezue, Varun Gangal, Cristina Garbacea, Tatsunori Hashimoto, Yufang Hou, Yacine Jernite, Harsh Jhamtani, Yangfeng Ji, Shailza Jolly, Dhruv Kumar, Faisal Ladhak, Aman Madaan, Mounica Maddela, Khyati Mahajan, Saad Mahamood, Bodhisattwa Prasad Majumder, Pedro Henrique Martins, Angelina McMillan-Major, Simon Mille, Emiel van Miltenburg, Moin Nadeem, Shashi Narayan, Vitaly Nikolaev, Rubungo Andre Niyongabo, Salomey Osei, Ankur P. Parikh, Laura Perez-Beltrachini, Niranjan Ramesh Rao, Vikas Raunak, Juan Diego Rodriguez, Sashank Santhanam, João Sedoc, Thibault Sellam, Samira Shaikh, Anastasia Shimorina, Marco Antonio Sobrevilla Cabezudo, Hendrik Strobelt, Nishant Subramani, Wei Xu, Diyi Yang, Akhila Yerukola, Jiawei Zhou:
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics. CoRR abs/2102.01672 (2021) - [i12]Khyathi Raghavi Chandu, Yonatan Bisk, Alan W. Black:
Grounding 'Grounding' in NLP. CoRR abs/2106.02192 (2021) - [i11]Sai Muralidhar Jayanthi, Kavya Nerella, Khyathi Raghavi Chandu, Alan W. Black:
CodemixedNLP: An Extensible and Open NLP Toolkit for Code-Mixing. CoRR abs/2106.06004 (2021) - [i10]Parul Chopra, Sai Krishna Rallabandi, Alan W. Black, Khyathi Raghavi Chandu:
Switch Point biased Self-Training: Re-purposing Pretrained Models for Code-Switching. CoRR abs/2111.01231 (2021) - 2020
- [i9]Khyathi Raghavi Chandu, Alan W. Black:
Style Variation as a Vantage Point for Code-Switching. CoRR abs/2005.00458 (2020) - [i8]Khyathi Raghavi Chandu, Piyush Sharma, Soravit Changpinyo, Ashish V. Thapliyal, Radu Soricut:
Weakly Supervised Content Selection for Improved Image Captioning. CoRR abs/2009.05175 (2020) - [i7]Khyathi Raghavi Chandu, Alan W. Black:
Dissecting the components and factors of Neural Text Generation. CoRR abs/2010.07279 (2020) - [i6]Khyathi Raghavi Chandu, Ruo-Ping Dong, Alan W. Black:
Reading Between the Lines: Exploring Infilling in Visual Narratives. CoRR abs/2010.13944 (2020) - 2019
- [i5]Sunayana Sitaram, Khyathi Raghavi Chandu, Sai Krishna Rallabandi, Alan W. Black:
A Survey of Code-switched Speech and Language Processing. CoRR abs/1904.00784 (2019) - [i4]Shrimai Prabhumoye, Khyathi Raghavi Chandu, Ruslan Salakhutdinov, Alan W. Black:
"My Way of Telling a Story": Persona based Grounded Story Generation. CoRR abs/1906.06401 (2019) - [i3]Ruo-Ping Dong, Khyathi Raghavi Chandu, Alan W. Black:
Induction and Reference of Entities in a Visual Story. CoRR abs/1909.09699 (2019) - 2018
- [i2]Soumya Wadhwa, Khyathi Raghavi Chandu, Eric Nyberg:
Comparative Analysis of Neural QA models on SQuAD. CoRR abs/1806.06972 (2018) - [i1]Khyathi Raghavi Chandu, Mary Arpita Pyreddy, Matthieu Felix, Narendra Nath Joshi:
Textually Enriched Neural Module Networks for Visual Question Answering. CoRR abs/1809.08697 (2018)
Coauthor Index
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