Using Reproductive Altruism to Evolve Multicellularity in Digital Organisms. - Jack Hessel; Sherri Goings (ECAL, 2013)

Evolving multicellularity in digital organisms through reproductive altruism. - Jack Hessel; Sherri Goings (GECCO (Companion), 2013)

Image Representations and New Domains in Neural Image Captioning. - Jack Hessel; Nicolas Savva; Michael J. Wilber (VL@EMNLP, 2015)

What do Vegans do in their Spare Time? Latent Interest Detection in Multi-Community Networks. - Jack Hessel; Alexandra Schofield; Lillian Lee; David M. Mimno (CoRR, 2015)

Science, AskScience, and BadScience: On the Coexistence of Highly Related Communities. - Jack Hessel; Chenhao Tan; Lillian Lee (ICWSM, 2016)

Cats and Captions vs. Creators and the Clock: Comparing Multimodal Content to Context in Predicting Relative Popularity. - Jack Hessel; Lillian Lee; David M. Mimno (WWW, 2017)

Quantifying the Visual Concreteness of Words and Topics in Multimodal Datasets. - Jack Hessel; David M. Mimno; Lillian Lee (NAACL-HLT, 2018)

A Case Study on Combining ASR and Visual Features for Generating Instructional Video Captions. - Jack Hessel; Bo Pang 001; Zhenhai Zhu; Radu Soricut (CoNLL, 2019)

Unsupervised Discovery of Multimodal Links in Multi-image, Multi-sentence Documents. - Jack Hessel; Lillian Lee; David Mimno (EMNLP/IJCNLP (1), 2019)

Something's Brewing! Early Prediction of Controversy-causing Posts from Discussion Features. - Jack Hessel; Lillian Lee (NAACL-HLT (1), 2019)

Does my multimodal model learn cross-modal interactions? It's harder to tell than you might think! - Jack Hessel; Lillian Lee (EMNLP (1), 2020)

Beyond Instructional Videos: Probing for More Diverse Visual-Textual Grounding on YouTube. - Jack Hessel; Zhenhai Zhu; Bo Pang 001; Radu Soricut (EMNLP (1), 2020)

Domain-Specific Lexical Grounding in Noisy Visual-Textual Documents. - Gregory Yauney; Jack Hessel; David Mimno (EMNLP (1), 2020)

How effective is BERT without word ordering? Implications for language understanding and data privacy. - Jack Hessel; Alexandra Schofield (ACL/IJCNLP (2), 2021)

CLIPScore: A Reference-free Evaluation Metric for Image Captioning. - Jack Hessel; Ari Holtzman; Maxwell Forbes; Ronan Le Bras 001; Yejin Choi 001 (EMNLP (1), 2021)

MERLOT: Multimodal Neural Script Knowledge Models. - Rowan Zellers; Ximing Lu; Jack Hessel; Youngjae Yu; Jae Sung Park; Jize Cao; Ali Farhadi; Yejin Choi 001 (NeurIPS, 2021)

MERLOT RESERVE: Neural Script Knowledge through Vision and Language and Sound. - Rowan Zellers; Jiasen Lu; Ximing Lu; Youngjae Yu; Yanpeng Zhao; Mohammadreza Salehi; Aditya Kusupati; Jack Hessel; Ali Farhadi; Yejin Choi 001 (CVPR, 2022)

The Abduction of Sherlock Holmes: A Dataset for Visual Abductive Reasoning. - Jack Hessel; Jena D. Hwang; Jae Sung Park; Rowan Zellers; Chandra Bhagavatula; Anna Rohrbach; Kate Saenko; Yejin Choi 001 (ECCV (36), 2022)

Symbolic Knowledge Distillation: from General Language Models to Commonsense Models. - Peter West; Chandra Bhagavatula; Jack Hessel; Jena D. Hwang; Liwei Jiang; Ronan Le Bras 001; Ximing Lu; Sean Welleck; Yejin Choi 001 (NAACL-HLT, 2022)

Reframing Human-AI Collaboration for Generating Free-Text Explanations. - Sarah Wiegreffe; Jack Hessel; Swabha Swayamdipta; Mark O. Riedl; Yejin Choi 001 (NAACL-HLT, 2022)

Connecting the Dots between Audio and Text without Parallel Data through Visual Knowledge Transfer. - Yanpeng Zhao; Jack Hessel; Youngjae Yu; Ximing Lu; Rowan Zellers; Yejin Choi 001 (NAACL-HLT, 2022)

QUARK: Controllable Text Generation with Reinforced Unlearning. - Ximing Lu; Sean Welleck; Jack Hessel; Liwei Jiang; Lianhui Qin; Peter West; Prithviraj Ammanabrolu; Yejin Choi 001 (NeurIPS, 2022)

Multimodal Knowledge Alignment with Reinforcement Learning. - Youngjae Yu; Jiwan Chung; Heeseung Yun; Jack Hessel; Jae Sung Park; Ximing Lu; Prithviraj Ammanabrolu; Rowan Zellers; Ronan Le Bras 001; Gunhee Kim; Yejin Choi 001 (CoRR, 2022)

SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization. - Hyunwoo Kim 002; Jack Hessel; Liwei Jiang; Ximing Lu; Youngjae Yu; Pei Zhou; Ronan Le Bras 001; Malihe Alikhani; Gunhee Kim; Maarten Sap; Yejin Choi 001 (CoRR, 2022)

Do Androids Laugh at Electric Sheep? Humor "Understanding" Benchmarks from The New Yorker Caption Contest. - Jack Hessel; Ana Marasovic; Jena D. Hwang; Lillian Lee; Jeff Da; Rowan Zellers; Robert Mankoff; Yejin Choi 001 (ACL (1), 2023)

Symbolic Chain-of-Thought Distillation: Small Models Can Also "Think" Step-by-Step. - Liunian Harold Li; Jack Hessel; Youngjae Yu; Xiang Ren 001; Kai-Wei Chang; Yejin Choi 001 (ACL (1), 2023)

Fusing Pre-Trained Language Models with Multimodal Prompts through Reinforcement Learning. - Youngjae Yu; Jiwan Chung; Heeseung Yun; Jack Hessel; Jae Sung Park; Ximing Lu; Rowan Zellers; Prithviraj Ammanabrolu; Ronan Le Bras 001; Gunhee Kim; Yejin Choi 001 (CVPR, 2023)

SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization. - Hyunwoo Kim 002; Jack Hessel; Liwei Jiang; Peter West; Ximing Lu; Youngjae Yu; Pei Zhou; Ronan Le Bras 001; Malihe Alikhani; Gunhee Kim; Maarten Sap; Yejin Choi 001 (EMNLP, 2023)

Reading Books is Great, But Not if You Are Driving! Visually Grounded Reasoning about Defeasible Commonsense Norms. - Seungju Han 002; Junhyeok Kim 002; Jack Hessel; Liwei Jiang; Jiwan Chung; Yejin Son; Yejin Choi 001; Youngjae Yu (EMNLP, 2023)

Text encoders bottleneck compositionality in contrastive vision-language models. - Amita Kamath; Jack Hessel; Kai-Wei Chang (EMNLP, 2023)

What's "up" with vision-language models? Investigating their struggle with spatial reasoning. - Amita Kamath; Jack Hessel; Kai-Wei Chang (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)

Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images. - Nitzan Bitton Guetta; Yonatan Bitton; Jack Hessel; Ludwig Schmidt; Yuval Elovici; Gabriel Stanovsky; Roy Schwartz 001 (ICCV, 2023)

Champagne: Learning Real-world Conversation from Large-Scale Web Videos. - Seungju Han 002; Jack Hessel; Nouha Dziri; Yejin Choi 001; Youngjae Yu (ICCV, 2023)

Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization. - Rajkumar Ramamurthy; Prithviraj Ammanabrolu; Kianté Brantley; Jack Hessel; Rafet Sifa; Christian Bauckhage; Hannaneh Hajishirzi; Yejin Choi 001 (ICLR, 2023)

VisIT-Bench: A Dynamic Benchmark for Evaluating Instruction-Following Vision-and-Language Models. - Yonatan Bitton; Hritik Bansal; Jack Hessel; Rulin Shao; Wanrong Zhu; Anas Awadalla; Josh Gardner 001; Rohan Taori; Ludwig Schmidt (NeurIPS, 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)

Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text. - Wanrong Zhu; Jack Hessel; Anas Awadalla; Samir Yitzhak Gadre; Jesse Dodge; Alex Fang; Youngjae Yu; Ludwig Schmidt; William Yang Wang; Yejin Choi 001 (NeurIPS, 2023)

Text encoders are performance bottlenecks in contrastive vision-language models. - Amita Kamath; Jack Hessel; Kai-Wei Chang (CoRR, 2023)

FunQA: Towards Surprising Video Comprehension. - Binzhu Xie; Sicheng Zhang; Zitang Zhou; Bo Li 080; Yuanhan Zhang; Jack Hessel; Jingkang Yang; Ziwei Liu 002 (CoRR, 2023)

OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models. - Anas Awadalla; Irena Gao; Josh Gardner 001; Jack Hessel; Yusuf Hanafy; Wanrong Zhu; Kalyani Marathe; Yonatan Bitton; Samir Yitzhak Gadre; Shiori Sagawa; Jenia Jitsev; Simon Kornblith; et al. (CoRR, 2023)

VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use. - Yonatan Bitton; Hritik Bansal; Jack Hessel; Rulin Shao; Wanrong Zhu; Anas Awadalla; Josh Gardner 001; Rohan Taori; Ludwig Schmidt (CoRR, 2023)

Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging. - Joel Jang; Seungone Kim; Bill Yuchen Lin; Yizhong Wang; Jack Hessel; Luke Zettlemoyer; Hannaneh Hajishirzi; Yejin Choi 001; Prithviraj Ammanabrolu (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)

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)

[inline-graphic not available: see fulltext] FunQA: Towards Surprising Video Comprehension. - Binzhu Xie; Sicheng Zhang; Zitang Zhou; Bo Li 080; Yuanhan Zhang; Jack Hessel; Jingkang Yang; Ziwei Liu 002 (ECCV (1), 2024)

Selective Vision is the Challenge for Visual Reasoning: A Benchmark for Visual Argument Understanding. - Jiwan Chung; Sungjae Lee 003; Minseo Kim; Seungju Han 002; Ashkan Yousefpour; Jack Hessel; Youngjae Yu (EMNLP, 2024)

How to Train Your Fact Verifier: Knowledge Transfer with Multimodal Open Models. - Jaeyoung Lee; Ximing Lu; Jack Hessel; Faeze Brahman; Youngjae Yu; Yonatan Bisk; Yejin Choi 001; Saadia Gabriel (EMNLP (Findings), 2024)

Tailoring Self-Rationalizers with Multi-Reward Distillation. - Sahana Ramnath; Brihi Joshi; Skyler Hallinan; Ximing Lu; Liunian Harold Li; Aaron Chan; Jack Hessel; Yejin Choi 001; Xiang Ren 001 (ICLR, 2024)

WildChat: 1M ChatGPT Interaction Logs in the Wild. - Wenting Zhao; Xiang Ren 001; Jack Hessel; Claire Cardie; Yejin Choi 001; Yuntian Deng (ICLR, 2024)

UNcommonsense Reasoning: Abductive Reasoning about Uncommon Situations. - Wenting Zhao; Justin T. Chiu; Jena D. Hwang; Faeze Brahman; Jack Hessel; Sanjiban Choudhury; Yejin Choi 001; Xiang Li 069; Alane Suhr (NAACL-HLT, 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)

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)

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)

WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild. - Yuntian Deng; Wenting Zhao; Jack Hessel; Xiang Ren 001; Claire Cardie; Yejin Choi 001 (CoRR, 2024)

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)

Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models. - Orion Weller; Benjamin Van Durme; Dawn J. Lawrie; Ashwin Paranjape; Yuhao Zhang; Jack Hessel (ICLR, 2025)

Investigating machine moral judgement through the Delphi experiment. - Liwei Jiang; Jena D. Hwang; Chandra Bhagavatula; Ronan Le Bras 001; Jenny T. Liang; Sydney Levine; Jesse Dodge; Keisuke Sakaguchi; Maxwell Forbes; Jack Hessel; Jonathan Borchardt; Taylor Sorensen; et al. (Nat. Mac. Intell., 2025)