"Answer ka type kya he?": Learning to Classify Questions in Code-Mixed Language. - Khyathi Chandu Raghavi; Manoj Kumar Chinnakotla; Manish Shrivastava 001 (WWW (Companion Volume), 2015)

Tackling Biomedical Text Summarization: OAQA at BioASQ 5B. - Khyathi Raghavi Chandu; Aakanksha Naik; Aditya Chandrasekar; Zi Yang; Niloy Gupta; Eric Nyberg (BioNLP, 2017)

WebShodh: A Code Mixed Factoid Question Answering System for Web. - Khyathi Raghavi Chandu; Manoj Kumar Chinnakotla; Alan W. Black; Manish Shrivastava 001 (CLEF, 2017)

"nee intention enti?" towards dialog act recognition in code-mixed conversations. - Divya Sai Jitta; Khyathi Raghavi Chandu; Harsha Pamidipalli; Radhika Mamidi (IALP, 2017)

Speech Synthesis for Mixed-Language Navigation Instructions. - Khyathi Raghavi Chandu; Sai Krishna Rallabandi; Sunayana Sitaram; Alan W. Black (INTERSPEECH, 2017)

Code-Mixed Question Answering Challenge: Crowd-sourcing Data and Techniques. - Khyathi Raghavi Chandu; Ekaterina Loginova; Vishal Gupta; Josef van Genabith; Günter Neumann; Manoj Kumar Chinnakotla; Eric Nyberg; Alan W. Black (CodeSwitch@ACL, 2018)

Language Informed Modeling of Code-Switched Text. - Khyathi Raghavi Chandu; Thomas Manzini; Sumeet Singh; Alan W. Black (CodeSwitch@ACL, 2018)

Tackling Code-Switched NER: Participation of CMU. - Parvathy Geetha; Khyathi Raghavi Chandu; Alan W. Black (CodeSwitch@ACL, 2018)

Comparative Analysis of Neural QA models on SQuAD. - Soumya Wadhwa; Khyathi Raghavi Chandu; Eric Nyberg (QA@ACL, 2018)

Textually Enriched Neural Module Networks for Visual Question Answering. - Khyathi Raghavi Chandu; Mary Arpita Pyreddy; Matthieu Felix; Narendra Nath Joshi (CoRR, 2018)

Storyboarding of Recipes: Grounded Contextual Generation. - Khyathi Raghavi Chandu; Eric Nyberg; Alan W. Black (DGS@ICLR, 2019)

A Survey of Code-switched Speech and Language Processing. - Sunayana Sitaram; Khyathi Raghavi Chandu; Sai Krishna Rallabandi; Alan W. Black (CoRR, 2019)

"My Way of Telling a Story": Persona based Grounded Story Generation. - Shrimai Prabhumoye; Khyathi Raghavi Chandu; Ruslan Salakhutdinov; Alan W. Black (CoRR, 2019)

Induction and Reference of Entities in a Visual Story. - Ruo-Ping Dong; Khyathi Raghavi Chandu; Alan W. Black (CoRR, 2019)

Reading Between the Lines: Exploring Infilling in Visual Narratives. - Khyathi Raghavi Chandu; Ruo-Ping Dong; Alan W. Black (EMNLP (1), 2020)

Style Variation as a Vantage Point for Code-Switching. - Khyathi Raghavi Chandu; Alan W. Black (INTERSPEECH, 2020)

Weakly Supervised Content Selection for Improved Image Captioning. - Khyathi Raghavi Chandu; Piyush Sharma; Soravit Changpinyo; Ashish V. Thapliyal; Radu Soricut (CoRR, 2020)

Dissecting the components and factors of Neural Text Generation. - Khyathi Raghavi Chandu; Alan W. Black (CoRR, 2020)

CodemixedNLP: An Extensible and Open NLP Toolkit for Code-Mixing. - Sai Muralidhar Jayanthi; Kavya Nerella; Khyathi Raghavi Chandu; Alan W. Black (CALCS@NAACL, 2021)

Grounding 'Grounding' in NLP. - Khyathi Raghavi Chandu; Yonatan Bisk; Alan W. Black (ACL/IJCNLP (Findings), 2021)

Switch Point biased Self-Training: Re-purposing Pretrained Models for Code-Switching. - Parul Chopra; Sai Krishna Rallabandi; Alan W. Black; Khyathi Raghavi Chandu (EMNLP (Findings), 2021)

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics. - Sebastian Gehrmann; Tosin P. Adewumi; Karmanya Aggarwal; Pawan Sasanka Ammanamanchi; Aremu Anuoluwapo; Antoine Bosselut; Khyathi Raghavi Chandu; Miruna-Adriana Clinciu; Dipanjan Das 001; Kaustubh D. Dhole; Wanyu Du; Esin Durmus; et al. (CoRR, 2021)

Denoising Large-Scale Image Captioning from Alt-text Data Using Content Selection Models. - Khyathi Raghavi Chandu; Piyush Sharma; Soravit Changpinyo; Ashish V. Thapliyal; Radu Soricut (COLING, 2022)

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code. - 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; et al. (CoRR, 2022)

Multilingual Multimodality: A Taxonomical Survey of Datasets, Techniques, Challenges and Opportunities. - Khyathi Raghavi Chandu; Alborz Geramifard (CoRR, 2022)

Needle in a Haystack: An Analysis of Finding Qualified Workers on MTurk for Summarization. - Lining Zhang; João Sedoc; Simon Mille; Yufang Hou 001; Sebastian Gehrmann; Daniel Deutsch; Elizabeth Clark; Yixin Liu 003; Miruna Clinciu; Saad Mahamood; Khyathi Raghavi Chandu (CoRR, 2022)

A Needle in a Haystack: An Analysis of High-Agreement Workers on MTurk for Summarization. - Lining Zhang; Simon Mille; Yufang Hou 001; Daniel Deutsch; Elizabeth Clark; Yixin Liu 003; Saad Mahamood; Sebastian Gehrmann; Miruna Clinciu; Khyathi Raghavi Chandu; João Sedoc (ACL (1), 2023)

Continual Dialogue State Tracking via Example-Guided Question Answering. - Hyundong Cho; Andrea Madotto; Zhaojiang Lin; Khyathi Raghavi Chandu; Satwik Kottur; Jing Xu; Jonathan May; Chinnadhurai Sankar (EMNLP, 2023)

Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. - 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; et al. (EMNLP, 2023)

NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation. - Peter West; Ronan Le Bras 001; Taylor Sorensen; Bill Yuchen Lin; Liwei Jiang; Ximing Lu; Khyathi Raghavi Chandu; Jack Hessel; Ashutosh Baheti; Chandra Bhagavatula; Yejin Choi 001 (EMNLP (Findings), 2023)

LOWRECORP: the Low-Resource NLG Corpus Building Challenge. - Khyathi Raghavi Chandu; David M. Howcroft; Dimitra Gkatzia; Yi-Ling Chung; Yufang Hou 001; Chris Chinenye Emezue; Pawan Rajpoot; Tosin P. Adewumi (INLG (Generation Challenges), 2023)

Localized Symbolic Knowledge Distillation for Visual Commonsense Models. - Jae Sung Park; Jack Hessel; Khyathi Raghavi Chandu; Paul Pu Liang; Ximing Lu; Peter West; Youngjae Yu; Qiuyuan Huang; Jianfeng Gao 001; Ali Farhadi; Yejin Choi 001 (NeurIPS, 2023)

How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources. - Yizhong Wang; Hamish Ivison; Pradeep Dasigi; Jack Hessel; Tushar Khot; Khyathi Raghavi Chandu; David Wadden; Kelsey MacMillan; Noah A. Smith; Iz Beltagy; Hannaneh Hajishirzi (NeurIPS, 2023)

Curriculum Script Distillation for Multilingual Visual Question Answering. - Khyathi Raghavi Chandu; Alborz Geramifard (CoRR, 2023)

Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs. - Da Yin; Faeze Brahman; Abhilasha Ravichander; Khyathi Raghavi Chandu; Kai-Wei Chang; Yejin Choi 001; Bill Yuchen Lin (CoRR, 2023)

OLMo: Accelerating the Science of Language Models. - 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; et al. (ACL (1), 2024)

Deal, or no deal (or who knows)? Forecasting Uncertainty in Conversations using Large Language Models. - Anthony Sicilia; Hyunwoo Kim 002; Khyathi Raghavi Chandu; Malihe Alikhani; Jack Hessel (ACL (Findings), 2024)

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. - 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; et al. (ACL (1), 2024)

Selective "Selective Prediction": Reducing Unnecessary Abstention in Vision-Language Reasoning. - Tejas Srinivasan; Jack Hessel; Tanmay Gupta; Bill Yuchen Lin; Yejin Choi 001; Jesse Thomason; Khyathi Raghavi Chandu (ACL (Findings), 2024)

Agent Lumos: Unified and Modular Training for Open-Source Language Agents. - Da Yin; Faeze Brahman; Abhilasha Ravichander; Khyathi Raghavi Chandu; Kai-Wei Chang; Yejin Choi 001; Bill Yuchen Lin (ACL (1), 2024)

Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals. - Yanai Elazar; Bhargavi Paranjape; Hao Peng 009; Sarah Wiegreffe; Khyathi Raghavi Chandu; Vivek Srikumar; Sameer Singh 001; Noah A. Smith (EMNLP (Findings), 2024)

The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning. - Bill Yuchen Lin; Abhilasha Ravichander; Ximing Lu; Nouha Dziri; Melanie Sclar; Khyathi Raghavi Chandu; Chandra Bhagavatula; Yejin Choi 001 (ICLR, 2024)

The Generative AI Paradox: "What It Can Create, It May Not Understand". - 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; et al. (ICLR, 2024)

On the Role of Summary Content Units in Text Summarization Evaluation. - Marcel Nawrath; Agnieszka Nowak; Tristan Ratz; Danilo C. Walenta; Juri Opitz; Leonardo F. R. Ribeiro; João Sedoc; Daniel Deutsch; Simon Mille; Yixin Liu 003; Sebastian Gehrmann; Lining Zhang; et al. (NAACL (Short Papers), 2024)

The Art of Saying No: Contextual Noncompliance in Language Models. - Faeze Brahman; Sachin Kumar 009; Vidhisha Balachandran; Pradeep Dasigi; Valentina Pyatkin; Abhilasha Ravichander; Sarah Wiegreffe; Nouha Dziri; Khyathi Raghavi Chandu; Jack Hessel; Yulia Tsvetkov; Noah A. Smith; et al. (NeurIPS, 2024)

DataComp-LM: In search of the next generation of training sets for language models. - Jeffrey Li; Alex Fang; Georgios Smyrnis; Maor Ivgi; Matt Jordan; Samir Yitzhak Gadre; Hritik Bansal; Etash Kumar Guha; Sedrick Scott Keh; Kushal Arora; Saurabh Garg; Rui Xin; et al. (NeurIPS, 2024)

OLMo: Accelerating the Science of Language Models. - 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; et al. (CoRR, 2024)

L3GO: Language Agents with Chain-of-3D-Thoughts for Generating Unconventional Objects. - Yutaro Yamada; Khyathi Raghavi Chandu; Bill Yuchen Lin; Jack Hessel; Ilker Yildirim; Yejin Choi 001 (CoRR, 2024)

RewardBench: Evaluating Reward Models for Language Modeling. - Nathan Lambert 001; Valentina Pyatkin; Jacob Morrison; LJ Miranda; Bill Yuchen Lin; Khyathi Raghavi Chandu; Nouha Dziri; Sachin Kumar 009; Tom Zick; Yejin Choi 001; Noah A. Smith; Hannaneh Hajishirzi (CoRR, 2024)

WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild. - Bill Yuchen Lin; Yuntian Deng; Khyathi Raghavi Chandu; Faeze Brahman; Abhilasha Ravichander; Valentina Pyatkin; Nouha Dziri; Ronan Le Bras 001; Yejin Choi 001 (CoRR, 2024)

Certainly Uncertain: A Benchmark and Metric for Multimodal Epistemic and Aleatoric Awareness. - Khyathi Raghavi Chandu; Linjie Li; Anas Awadalla; Ximing Lu; Jae Sung Park; Jack Hessel; Lijuan Wang; Yejin Choi 001 (CoRR, 2024)

WildHallucinations: Evaluating Long-form Factuality in LLMs with Real-World Entity Queries. - Wenting Zhao; Tanya Goyal; Yu Ying Chiu; Liwei Jiang; Benjamin Newman; Abhilasha Ravichander; Khyathi Raghavi Chandu; Ronan Le Bras 001; Claire Cardie; Yuntian Deng; Yejin Choi 001 (CoRR, 2024)

RESTOR: Knowledge Recovery through Machine Unlearning. - Keivan Rezaei; Khyathi Raghavi Chandu; Soheil Feizi; Yejin Choi 001; Faeze Brahman; Abhilasha Ravichander (CoRR, 2024)

Effective Anchoring of Multimodal Narrative Generation - Khyathi Raghavi Chandu (2024)

Synthetic Visual Genome. - Jae Sung Park; Zixian Ma; Linjie Li; Chenhao Zheng; Cheng-Yu Hsieh; Ximing Lu; Khyathi Raghavi Chandu; Quan Kong; Norimasa Kobori; Ali Farhadi; Yejin Choi 001; Ranjay Krishna (CVPR, 2025)

CertainlyUncertain: A Benchmark and Metric for Multimodal Epistemic and Aleatoric Awareness. - Khyathi Raghavi Chandu; Linjie Li; Anas Awadalla; Ximing Lu; Jae Sung Park; Jack Hessel; Lijuan Wang; Yejin Choi 001 (ICLR, 2025)

WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild. - Bill Yuchen Lin; Yuntian Deng; Khyathi Raghavi Chandu; Abhilasha Ravichander; Valentina Pyatkin; Nouha Dziri; Ronan Le Bras 001; Yejin Choi 001 (ICLR, 2025)

AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text. - Ximing Lu; Melanie Sclar; Skyler Hallinan; Niloofar Mireshghallah; Jiacheng Liu 010; Seungju Han 002; Allyson Ettinger; Liwei Jiang; Khyathi Raghavi Chandu; Nouha Dziri; Yejin Choi 001 (ICLR, 2025)

RewardBench: Evaluating Reward Models for Language Modeling. - Nathan Lambert 001; Valentina Pyatkin; Jacob Morrison; Lester James V. Miranda; Bill Yuchen Lin; Khyathi Raghavi Chandu; Nouha Dziri; Sachin Kumar 009; Tom Zick; Yejin Choi 001; Noah A. Smith; Hannaneh Hajishirzi (NAACL (Findings), 2025)

RESTOR: Knowledge Recovery in Machine Unlearning. - Keivan Rezaei; Khyathi Raghavi Chandu; Soheil Feizi; Yejin Choi 001; Faeze Brahman; Abhilasha Ravichander (Trans. Mach. Learn. Res., 2025)

Magistral. - Abhinav Rastogi; Albert Q. Jiang; Andy Lo; Gabrielle Berrada; Guillaume Lample; Jason Rute; Joep Barmentlo; Karmesh Yadav; Kartik Khandelwal; Khyathi Raghavi Chandu; Léonard Blier; Lucile Saulnier; et al. (CoRR, 2025)

Voxtral. - Alexander H. Liu; Andy Ehrenberg; Andy Lo; Clément Denoix; Corentin Barreau; Guillaume Lample; Jean-Malo Delignon; Khyathi Raghavi Chandu; Patrick von Platen; Pavankumar Reddy Muddireddy; Sanchit Gandhi; Soham Ghosh; et al. (CoRR, 2025)