Xiaochuang Han
Xiaochuang Han
Verified email at - Homepage
Cited by
Cited by
Unsupervised domain adaptation of contextualized embeddings for sequence labeling
X Han, J Eisenstein
arXiv preprint arXiv:1904.02817, 2019
Explaining black box predictions and unveiling data artifacts through influence functions
X Han, BC Wallace, Y Tsvetkov
arXiv preprint arXiv:2005.06676, 2020
Interactional stancetaking in online forums
SF Kiesling, U Pavalanathan, J Fitzpatrick, X Han, J Eisenstein
Computational Linguistics 44 (4), 683-718, 2018
Fortifying toxic speech detectors against veiled toxicity
X Han, Y Tsvetkov
arXiv preprint arXiv:2010.03154, 2020
Influence tuning: Demoting spurious correlations via instance attribution and instance-driven updates
X Han, Y Tsvetkov
arXiv preprint arXiv:2110.03212, 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
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
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
No permanent friends or enemies: Tracking relationships between nations from news
X Han, E Choi, C Tan
arXiv preprint arXiv:1904.08950, 2019
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
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
Can Language Models Solve Graph Problems in Natural Language?
H Wang, S Feng, T He, Z Tan, X Han, Y Tsvetkov
arXiv preprint arXiv:2305.10037, 2023
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
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
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
In-Context Alignment: Chat with Vanilla Language Models Before Fine-Tuning
X Han
arXiv preprint arXiv:2308.04275, 2023
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
ORCA: Interpreting Prompted Language Models via Locating Supporting Evidence in the Ocean of Pretraining Data
X Han, Y Tsvetkov
Unsupervised domain adaptation of contextualized embeddings for sequence labeling
H Xiaochuang, E Jacob
Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019
The system can't perform the operation now. Try again later.
Articles 1–19