Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions. - Peter Clark; Oren Etzioni; Tushar Khot; Ashish Sabharwal; Oyvind Tafjord; Peter D. Turney; Daniel Khashabi (AAAI, 2016)

Semantic Parsing to Probabilistic Programs for Situated Question Answering. - Jayant Krishnamurthy; Oyvind Tafjord; Aniruddha Kembhavi (EMNLP, 2016)

Moving beyond the Turing Test with the Allen AI Science Challenge. - Carissa Schoenick; Peter Clark; Oyvind Tafjord; Peter D. Turney; Oren Etzioni (Commun. ACM, 2017)

Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge. - Peter Clark; Isaac Cowhey; Oren Etzioni; Tushar Khot; Ashish Sabharwal; Carissa Schoenick; Oyvind Tafjord (CoRR, 2018)

AllenNLP: A Deep Semantic Natural Language Processing Platform. - Matt Gardner 001; Joel Grus; Mark Neumann; Oyvind Tafjord; Pradeep Dasigi; Nelson F. Liu; Matthew E. Peters; Michael Schmitz 002; Luke Zettlemoyer (CoRR, 2018)

Declarative Question Answering over Knowledge Bases Containing Natural Language Text with Answer Set Programming. - Arindam Mitra; Peter Clark; Oyvind Tafjord; Chitta Baral (AAAI, 2019)

QUAREL: A Dataset and Models for Answering Questions about Qualitative Relationships. - Oyvind Tafjord; Peter Clark; Matt Gardner 001; Wen-tau Yih; Ashish Sabharwal (AAAI, 2019)

Reasoning Over Paragraph Effects in Situations. - Kevin Lin; Oyvind Tafjord; Peter Clark; Matt Gardner 001 (MRQA@EMNLP, 2019)

QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions. - Oyvind Tafjord; Matt Gardner 001; Kevin Lin; Peter Clark (EMNLP/IJCNLP (1), 2019)

Extracting evidence of supplement-drug interactions from literature. - Lucy Lu Wang; Oyvind Tafjord; Sarthak Jain; Arman Cohan; Sam Skjonsberg; Carissa Schoenick; Nick Botner; Waleed Ammar (CoRR, 2019)

SUPP.AI: finding evidence for supplement-drug interactions. - Lucy Lu Wang; Oyvind Tafjord; Arman Cohan; Sarthak Jain; Sam Skjonsberg; Carissa Schoenick; Nick Botner; Waleed Ammar (ACL (demo), 2020)

UnifiedQA: Crossing Format Boundaries With a Single QA System. - Daniel Khashabi; Sewon Min; Tushar Khot; Ashish Sabharwal; Oyvind Tafjord; Peter Clark; Hannaneh Hajishirzi (EMNLP (Findings), 2020)

"You are grounded!": Latent Name Artifacts in Pre-trained Language Models. - Vered Shwartz; Rachel Rudinger; Oyvind Tafjord (EMNLP (1), 2020)

Transformers as Soft Reasoners over Language. - Peter Clark; Oyvind Tafjord; Kyle Richardson 001 (IJCAI, 2020)

Multi-class Hierarchical Question Classification for Multiple Choice Science Exams. - Dongfang Xu; Peter A. Jansen; Jaycie Martin; Zhengnan Xie; Vikas Yadav; Harish Tayyar Madabushi; Oyvind Tafjord; Peter Clark (LREC, 2020)

Leap-Of-Thought: Teaching Pre-Trained Models to Systematically Reason Over Implicit Knowledge. - Alon Talmor; Oyvind Tafjord; Peter Clark; Yoav Goldberg; Jonathan Berant (NeurIPS, 2020)

From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project. - Peter Clark; Oren Etzioni; Tushar Khot; Daniel Khashabi; Bhavana Dalvi Mishra; Kyle Richardson 001; Ashish Sabharwal; Carissa Schoenick; Oyvind Tafjord; Niket Tandon; Sumithra Bhakthavatsalam; Dirk Groeneveld; et al. (AI Mag., 2020)

UnifiedQA: Crossing Format Boundaries With a Single QA System. - Daniel Khashabi; Tushar Khot; Ashish Sabharwal; Oyvind Tafjord; Peter Clark; Hannaneh Hajishirzi (CoRR, 2020)

Teaching Pre-Trained Models to Systematically Reason Over Implicit Knowledge. - Alon Talmor; Oyvind Tafjord; Peter Clark; Yoav Goldberg; Jonathan Berant (CoRR, 2020)

ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language. - Oyvind Tafjord; Bhavana Dalvi; Peter Clark (ACL/IJCNLP (Findings), 2021)

"Let Your Characters Tell Their Story": A Dataset for Character-Centric Narrative Understanding. - Faeze Brahman; Meng Huang; Oyvind Tafjord; Chao Zhao 002; Mrinmaya Sachan; Snigdha Chaturvedi (EMNLP (Findings), 2021)

Explaining Answers with Entailment Trees. - Bhavana Dalvi; Peter Jansen 001; Oyvind Tafjord; Zhengnan Xie; Hannah Smith; Leighanna Pipatanangkura; Peter Clark (EMNLP (1), 2021)

BeliefBank: Adding Memory to a Pre-Trained Language Model for a Systematic Notion of Belief. - Nora Kassner; Oyvind Tafjord; Hinrich Schütze; Peter Clark (EMNLP (1), 2021)

Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge. - Sumithra Bhakthavatsalam; Daniel Khashabi; Tushar Khot; Bhavana Dalvi Mishra; Kyle Richardson 001; Ashish Sabharwal; Carissa Schoenick; Oyvind Tafjord; Peter Clark (CoRR, 2021)

Enriching a Model's Notion of Belief using a Persistent Memory. - Nora Kassner; Oyvind Tafjord; Hinrich Schütze; Peter Clark (CoRR, 2021)

General-Purpose Question-Answering with Macaw. - Oyvind Tafjord; Peter Clark (CoRR, 2021)

LILA: A Unified Benchmark for Mathematical Reasoning. - Swaroop Mishra; Matthew Finlayson; Pan Lu; Leonard Tang; Sean Welleck; Chitta Baral; Tanmay Rajpurohit; Oyvind Tafjord; Ashish Sabharwal; Peter Clark; Ashwin Kalyan (EMNLP, 2022)

Towards Teachable Reasoning Systems: Using a Dynamic Memory of User Feedback for Continual System Improvement. - Bhavana Dalvi Mishra; Oyvind Tafjord; Peter Clark (EMNLP, 2022)

Entailer: Answering Questions with Faithful and Truthful Chains of Reasoning. - Oyvind Tafjord; Bhavana Dalvi Mishra; Peter Clark (EMNLP, 2022)

Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering. - Pan Lu; Swaroop Mishra; Tanglin Xia; Liang Qiu 001; Kai-Wei Chang; Song-Chun Zhu; Oyvind Tafjord; Peter Clark; Ashwin Kalyan (NeurIPS, 2022)

Towards Teachable Reasoning Systems. - Bhavana Dalvi; Oyvind Tafjord; Peter Clark (CoRR, 2022)

Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering. - Pan Lu; Swaroop Mishra; Tony Xia; Liang Qiu 001; Kai-Wei Chang; Song-Chun Zhu; Oyvind Tafjord; Peter Clark; Ashwin Kalyan (CoRR, 2022)

Language Models with Rationality. - Nora Kassner; Oyvind Tafjord; Ashish Sabharwal; Kyle Richardson 001; Hinrich Schütze; Peter Clark (EMNLP, 2023)

Increasing Probability Mass on Answer Choices Does Not Always Improve Accuracy. - Sarah Wiegreffe; Matthew Finlayson; Oyvind Tafjord; Peter Clark; Ashish Sabharwal (EMNLP, 2023)

Attentiveness to Answer Choices Doesn't Always Entail High QA Accuracy. - Sarah Wiegreffe; Matthew Finlayson; Oyvind Tafjord; Peter Clark; Ashish Sabharwal (CoRR, 2023)

CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and Generalization. - Bodhisattwa Prasad Majumder; Bhavana Dalvi Mishra; Peter A. Jansen; Oyvind Tafjord; Niket Tandon; Li Zhang 039; Chris Callison-Burch; Peter Clark (CoRR, 2023)

BaRDa: A Belief and Reasoning Dataset that Separates Factual Accuracy and Reasoning Ability. - Peter Clark; Bhavana Dalvi Mishra; Oyvind Tafjord (CoRR, 2023)

Catwalk: A Unified Language Model Evaluation Framework for Many Datasets. - Dirk Groeneveld; Anas Awadalla; Iz Beltagy; Akshita Bhagia; Ian Magnusson; Hao Peng 009; Oyvind Tafjord; Pete Walsh; Kyle Richardson 001; Jesse Dodge (CoRR, 2023)

Faithful Reasoning over Scientific Claims. - Neset Özkan Tan; Niket Tandon; David Wadden; Oyvind Tafjord; Mark Gahegan; Michael Witbrock (AAAI Spring Symposia, 2024)

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)

Digital Socrates: Evaluating LLMs through Explanation Critiques. - Yuling Gu; Oyvind Tafjord; Peter Clark (ACL (1), 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)

Enhancing Systematic Decompositional Natural Language Inference Using Informal Logic. - Nathaniel Weir; Kate Sanders 002; Orion Weller; Shreya Sharma 010; Dongwei Jiang; Zhengping Jiang; Bhavana Dalvi Mishra; Oyvind Tafjord; Peter A. Jansen; Peter Clark; Benjamin Van Durme (EMNLP, 2024)

DiscoveryWorld: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents. - Peter A. Jansen; Marc-Alexandre Côté; Tushar Khot; Erin Bransom; Bhavana Dalvi Mishra; Bodhisattwa Prasad Majumder; Oyvind Tafjord; Peter Clark (NeurIPS, 2024)

Paloma: A Benchmark for Evaluating Language Model Fit. - Ian Magnusson; Akshita Bhagia; Valentin Hofmann; Luca Soldaini; Ananya Harsh Jha; Oyvind Tafjord; Dustin Schwenk; Evan Pete Walsh; Yanai Elazar; Kyle Lo; Dirk Groeneveld; Iz Beltagy; 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)

Answer, Assemble, Ace: Understanding How Transformers Answer Multiple Choice Questions. - Sarah Wiegreffe; Oyvind Tafjord; Yonatan Belinkov; Hannaneh Hajishirzi; Ashish Sabharwal (CoRR, 2024)

OLMoE: Open Mixture-of-Experts Language Models. - Niklas Muennighoff; Luca Soldaini; Dirk Groeneveld; Kyle Lo; Jacob Morrison; Sewon Min; Weijia Shi; Pete Walsh; Oyvind Tafjord; Nathan Lambert 001; Yuling Gu; Shane Arora; et al. (CoRR, 2024)

SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMs. - Yuling Gu; Oyvind Tafjord; Hyunwoo Kim 002; Jared Moore; Ronan Le Bras 001; Peter Clark; Yejin Choi 001 (CoRR, 2024)

TÜLU 3: Pushing Frontiers in Open Language Model Post-Training. - Nathan Lambert 001; Jacob Morrison; Valentina Pyatkin; Shengyi Huang; Hamish Ivison; Faeze Brahman; Lester James V. Miranda; Alisa Liu; Nouha Dziri; Shane Lyu; Yuling Gu; Saumya Malik; et al. (CoRR, 2024)

Establishing Task Scaling Laws via Compute-Efficient Model Ladders. - Akshita Bhagia; Jiacheng Liu 010; Alexander Wettig; David Heineman; Oyvind Tafjord; Ananya Harsh Jha; Luca Soldaini; Noah A. Smith; Dirk Groeneveld; Pang Wei Koh; Jesse Dodge; Hannaneh Hajishirzi (CoRR, 2024)

CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation. - Peter Jansen 001; Oyvind Tafjord; Marissa Radensky; Pao Siangliulue; Tom Hope; Bhavana Dalvi Mishra; Bodhisattwa Prasad Majumder; Daniel S. Weld; Peter Clark (ACL (Findings), 2025)

OLMoE: Open Mixture-of-Experts Language Models. - Niklas Muennighoff; Luca Soldaini; Dirk Groeneveld; Kyle Lo; Jacob Morrison; Sewon Min; Weijia Shi; Evan Pete Walsh; Oyvind Tafjord; Nathan Lambert 001; Yuling Gu; Shane Arora; et al. (ICLR, 2025)

From Models to Microtheories: Distilling a Model's Topical Knowledge for Grounded Question-Answering. - Nathaniel Weir; Bhavana Dalvi Mishra; Orion Weller; Oyvind Tafjord; Sam Hornstein; Alexander Sabol; Peter A. Jansen; Benjamin Van Durme; Peter Clark (ICLR, 2025)

Answer, Assemble, Ace: Understanding How LMs Answer Multiple Choice Questions. - Sarah Wiegreffe; Oyvind Tafjord; Yonatan Belinkov; Hannaneh Hajishirzi; Ashish Sabharwal (ICLR, 2025)

OLMES: A Standard for Language Model Evaluations. - Yuling Gu; Oyvind Tafjord; Bailey Kuehl; Dany Haddad; Jesse Dodge; Hannaneh Hajishirzi (NAACL (Findings), 2025)

2 OLMo 2 Furious. - Team OLMo; Pete Walsh; Luca Soldaini; Dirk Groeneveld; Kyle Lo; Shane Arora; Akshita Bhagia; Yuling Gu; Shengyi Huang; Matt Jordan; Nathan Lambert 001; Dustin Schwenk; et al. (CoRR, 2025)

DataDecide: How to Predict Best Pretraining Data with Small Experiments. - Ian Magnusson; Nguyen Tai; Ben Bogin; David Heineman; Jena D. Hwang; Luca Soldaini; Akshita Bhagia; Jiacheng Liu 010; Dirk Groeneveld; Oyvind Tafjord; Noah A. Smith; Pang Wei Koh; et al. (CoRR, 2025)

Because we have LLMs, we Can and Should Pursue Agentic Interpretability. - Been Kim; John Hewitt; Neel Nanda; Noah Fiedel; Oyvind Tafjord (CoRR, 2025)