Dziri, Nouha

Self-Refine: Iterative Refinement with Self-Feedback

Madaan, A., Tandon, N., Gupta, P., Hallinan, S., Gao, L., Wiegreffe, S., Alon, U., Dziri, N., Prabhumoye, S., Yang, Y., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2,314

Faith and Fate: Limits of Transformers on Compositionality

Dziri, N., Lu, X., Sclar, M., Li, X. (., Jiang, L., Lin, B. Y., Welleck, S., West, P., Bhagavatula, C., Bras, R. L., et al. (2023) · Advances in Neural Information Processing Systems 36

Syntax, Semantics, Linguistic VariationPhilosophy and Theoretical Science

Cited by 335

Faith and Fate: Limits of Transformers on Compositionality

Dziri, N., Lu, X., Sclar, M., Li, X. L., Jiang, L., Lin, B. Y., West, P., Bhagavatula, C., Bras, R. L., Hwang, J. D., et al. (2023) · arXiv

Syntax, Semantics, Linguistic VariationPhilosophy and Theoretical Science

Cited by 124

On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models?

Dziri, N., Milton, S., Yu, M., Zaiane, O., & Reddy, S. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Speech and dialogue systemsNatural Language Processing Techniques

Cited by 121

Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)

Jiang, L., Chai, Y., Li, M., Liu, M., Fok, R., Dziri, N., Tsvetkov, Y., Sap, M., Albalak, A., & Choi, Y. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 107

Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Grounding

Dziri, N., Madotto, A., Zaïane, O., & Bose, A. J. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Speech and dialogue systemsTopic Modeling

Cited by 81

Evaluating Attribution in Dialogue Systems: The BEGIN Benchmark

Dziri, N., Rashkin, H., Linzen, T., & Reitter, D. (2021) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 47

Fine-Grained Human Feedback Gives Better Rewards for Language Model Training

Wu, Z., Hu, Y., Shi, W., Dziri, N., Suhr, A., Ammanabrolu, P., Smith, N. A., Ostendorf, M., & Hajishirzi, H. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 40

WildGuard: Open One-stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs

Han, S., Rao, K., Ettinger, A., Jiang, L., Lin, B. Y., Lambert, N., Choi, Y., & Dziri, N. (2024) · Advances in Neural Information Processing Systems 37

Adversarial Robustness in Machine LearningHate Speech and Cyberbullying Detection

Cited by 36

On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models?

Dziri, N., Milton, S., Yu, M., Zaiane, O., & Reddy, S. (2022) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 13

RewardBench: Evaluating Reward Models for Language Modeling

Lambert, N., Pyatkin, V., Morrison, J., Miranda, L., Lin, B. Y., Chandu, K., Dziri, N., Kumar, S., Zick, T., Choi, Y., et al. (2025) · Findings of the Association for Computational Linguistics: NAACL 2025

Natural Language Processing TechniquesTopic Modeling

Cited by 13

TÜLU 3: Pushing Frontiers in Open Language Model Post-Training

Lambert, N., Morrison, J., Pyatkin, V., Huang, S., Ivison, H., Brahman, F., Miranda, L. J. V., Liu, A., Dziri, N., Lyu, S., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 12

The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning

Lin, B. Y., Ravichander, A., Lu, X., Dziri, N., Sclar, M., Chandu, K., Bhagavatula, C., & Choi, Y. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 11

Elastic Weight Removal for Faithful and Abstractive Dialogue Generation

Daheim, N., Dziri, N., Sachan, M., Gurevych, I., & Ponti, E. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Speech and dialogue systemsTopic Modeling

Cited by 7

RewardBench: Evaluating Reward Models for Language Modeling

Lambert, N., Pyatkin, V., Morrison, J., Miranda, L., Lin, B. Y., Chandu, K., Dziri, N., Kumar, S., Zick, T., Choi, Y., et al. (2024) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 5

WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild

Lin, B. Y., Deng, Y., Chandu, K., Brahman, F., Ravichander, A., Pyatkin, V., Dziri, N., Bras, R. L., & Choi, Y. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4

2 OLMo 2 Furious

OLMo, T., Walsh, P., Soldaini, L., Groeneveld, D., Lo, K., Arora, S., Bhagia, A., Gu, Y., Huang, S., Jordan, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

Elastic Weight Removal for Faithful and Abstractive Dialogue Generation

Daheim, N., Dziri, N., Sachan, M., Gurevych, I., & Ponti, E. M. (2023) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 0

OpenAgentSafety: A Comprehensive Framework for Evaluating Real-World AI Agent Safety

Vijayvargiya, S., Soni, A. B., Zhou, X., Wang, Z. Z., Dziri, N., Neubig, G., & Sap, M. (2025) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 0