Unsupervised domain adaptation of contextualized embeddings for sequence labeling X Han, J Eisenstein arXiv preprint arXiv:1904.02817, 2019 | 198 | 2019 |
Explaining black box predictions and unveiling data artifacts through influence functions X Han, BC Wallace, Y Tsvetkov arXiv preprint arXiv:2005.06676, 2020 | 165 | 2020 |
Interactional stancetaking in online forums SF Kiesling, U Pavalanathan, J Fitzpatrick, X Han, J Eisenstein Computational Linguistics 44 (4), 683-718, 2018 | 82 | 2018 |
Fortifying toxic speech detectors against veiled toxicity X Han, Y Tsvetkov arXiv preprint arXiv:2010.03154, 2020 | 67 | 2020 |
Can language models solve graph problems in natural language? H Wang, S Feng, T He, Z Tan, X Han, Y Tsvetkov Advances in Neural Information Processing Systems 36, 2024 | 57 | 2024 |
Trusting your evidence: Hallucinate less with context-aware decoding W Shi, X Han, M Lewis, Y Tsvetkov, L Zettlemoyer, SW Yih arXiv preprint arXiv:2305.14739, 2023 | 49 | 2023 |
Ssd-lm: Semi-autoregressive simplex-based diffusion language model for text generation and modular control X Han, S Kumar, Y Tsvetkov arXiv preprint arXiv:2210.17432, 2022 | 38 | 2022 |
Influence tuning: Demoting spurious correlations via instance attribution and instance-driven updates X Han, Y Tsvetkov arXiv preprint arXiv:2110.03212, 2021 | 32 | 2021 |
Mind your POV: convergence of articles and editors towards Wikipedia's neutrality norm U Pavalanathan, X Han, J Eisenstein Proceedings of the ACM on Human-Computer Interaction 2 (CSCW), 1-23, 2018 | 26 | 2018 |
Toward Human Readable Prompt Tuning: Kubrick's The Shining is a good movie, and a good prompt too? W Shi, X Han, H Gonen, A Holtzman, Y Tsvetkov, L Zettlemoyer arXiv preprint arXiv:2212.10539, 2022 | 23 | 2022 |
Orca: Interpreting prompted language models via locating supporting data evidence in the ocean of pretraining data X Han, Y Tsvetkov arXiv preprint arXiv:2205.12600, 2022 | 23 | 2022 |
Predicting the suitability of service animals using instrumented dog toys C Byrne, J Zuerndorfer, L Freil, X Han, A Sirolly, S Cilliland, T Starner, ... Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018 | 22 | 2018 |
Understanding in-context learning via supportive pretraining data X Han, D Simig, T Mihaylov, Y Tsvetkov, A Celikyilmaz, T Wang arXiv preprint arXiv:2306.15091, 2023 | 20 | 2023 |
Tuning language models by proxy A Liu, X Han, Y Wang, Y Tsvetkov, Y Choi, NA Smith arXiv preprint arXiv:2401.08565, 2024 | 15 | 2024 |
No permanent friends or enemies: Tracking relationships between nations from news X Han, E Choi, C Tan arXiv preprint arXiv:1904.08950, 2019 | 12 | 2019 |
On the zero-shot generalization of machine-generated text detectors X Pu, J Zhang, X Han, Y Tsvetkov, T He arXiv preprint arXiv:2310.05165, 2023 | 9 | 2023 |
Technology for working dogs MM Jackson, C Byrne, L Freil, G Valentin, J Zuerndorfer, C Zeagler, ... Proceedings of the Fifth International Conference on Animal-Computer …, 2018 | 9 | 2018 |
Ssd-2: Scaling and inference-time fusion of diffusion language models X Han, S Kumar, Y Tsvetkov, M Ghazvininejad arXiv preprint arXiv:2305.14771, 2023 | 5 | 2023 |
In-Context Alignment: Chat with Vanilla Language Models Before Fine-Tuning X Han arXiv preprint arXiv:2308.04275, 2023 | 4 | 2023 |
What Constitutes a Faithful Summary? Preserving Author Perspectives in News Summarization Y Liu, S Feng, X Han, V Balachandran, CY Park, S Kumar, Y Tsvetkov arXiv preprint arXiv:2311.09741, 2023 | | 2023 |