Tianlu Wang

ASTRO: Teaching Language Models to Reason by Reflecting and Backtracking In-Context
Joongwon Kim, Anirudh Goyal, Liang Tan, Hannaneh Hajishirzi, Srinivasan Iyer, Tianlu Wang.

J1: Incentivizing thinking in llm-as-a-judge via reinforcement learning
Chenxi Whitehouse, Tianlu Wang, Ping Yu, Xian Li, Jason Weston, Ilia Kulikov, Swarnadeep Saha.

Multi-Token Attention
Olga Golovneva, Tianlu Wang, Jason Weston, Sainbayar Sukhbaatar. COLM 2025

Learning to plan & reason for evaluation with thinking-llm-as-a-judge
Swarnadeep Saha, Xian Li, Marjan Ghazvininejad, Jason Weston, Tianlu Wang. ICML 2025

Self-taught evaluators
Tianlu Wang,Tianlu Wang, Ilia Kulikov, Olga Golovneva, Ping Yu, Weizhe Yuan, Jane Dwivedi-Yu, Richard Yuanzhe Pang, Maryam Fazel-Zarandi, Jason Weston, Xian Li.

Contextual Position Encoding: Learning to Count What's Important
Olga Golovneva, Tianlu Wang, Jason Weston, Sainbayar Sukhbaatar.

Chameleon: Mixed-modal early-fusion foundation models
Chameleon Team.

Shepherd: A critic for language model generation
Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan, Sean O'Brien, Ramakanth Pasunuru, Jane Dwivedi-Yu, Olga Golovneva, Luke Zettlemoyer, Maryam Fazel-Zarandi, Asli Celikyilmaz.

Efficient tool use with chain-of-abstraction reasoning
Silin Gao, Jane Dwivedi-Yu, Ping Yu, Xiaoqing Ellen Tan, Ramakanth Pasunuru, Olga Golovneva, Koustuv Sinha, Asli Celikyilmaz, Antoine Bosselut, Tianlu Wang. COLING 2025

Understanding in-context learning via supportive pretraining data
Xiaochuang Han, Daniel Simig, Todor Mihaylov, Yulia Tsvetkov, Asli Celikyilmaz, Tianlu Wang. ACL 2023

OPT: Open Pre-trained Transformer Language Models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, Todor Mihaylov, Myle Ott, Sam Shleifer, Kurt Shuster, Daniel Simig, Punit Singh Koura, Anjali Sridhar, Tianlu Wang, Luke Zettlemoyer

Few-shot Learning with Multilingual Language Models
Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, Tianlu Wang, Shuohui Chen, Daniel Simig, Myle Ott, Naman Goyal, Shruti Bhosale, Jingfei Du, Ramakanth Pasunuru, Sam Shleifer, Punit Singh Koura, Vishrav Chaudhary, Brian O'Horo, Jeff Wang, Luke Zettlemoyer, Zornitsa Kozareva, Mona Diab, Veselin Stoyanov, Xian Li. EMNLP 2022

Identifying and mitigating spurious correlations for improving robustness in NLP models
Tianlu Wang, Rohit Sridhar, Diyi Yang, Xuezhi Wang
North American Chapter of the Association for Computational Linguistics. NAACL 2022 Findings. Seattle, Washington + Online. July. 2022
[arxiv] [code] [bibtex]

VisualNews : Benchmark and Challenges in Entity-aware Image Captioning
Fuxiao Liu, Yinghan Wang, Tianlu Wang, Vicente Ordonez
Empirical Methods in Natural Language Processing. EMNLP 2021. Punta Cana, Dominican Republic. Nov. 2021
[arxiv] [code] [bibtex]

General Multi-label Image Classification with Transformers
Jack Lanchantin, Tianlu Wang, Vicente Ordonez, Yanjun Qi.
Intl. Conference on Computer Vision and Pattern Recognition. CVPR 2021. Nashville, TN. June 2021.
[arxiv] [bibtex]

CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation
Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Lee, Jilin Chen, Alex Beutel, Ed Chi
Empirical Methods in Natural Language Processing. EMNLP 2020. short. Virtual Conference. Nov. 2020
[arxiv] [bibtex]

Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation
Tianlu Wang, Xi Victoria Lin, Nazneen Fatema Rajani, Bryan McCann, Vicente Ordonez, Caiming Xiong
Association for Computational Linguistics. ACL 2020. Virtual Conference. July 2020.
[arxiv][code][bibtex][debiased embeddings]

Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations
Tianlu Wang, Jieyu Zhao, Mark Yatskar, Kai-Wei Chang, Vicente Ordonez.
International Conference on Computer Vision. ICCV 2019. Seoul, South Korea. October 2019.
[arxiv][code][bibtex]

Gender Bias in Contextualized Word Embeddings
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Ryan Cotterell, Vicente Ordonez, Kai-Wei Chang.
North American Chapter of the Association for Computational Linguistics. NAACL 2019. short.
Minneapolis, Minnesota. June 2019.
[arXiv][bibtex]

Feedback-prop: Convolutional Neural Network Inference under Partial Evidence
Tianlu Wang, Kota Yamaguchi, Vicente Ordonez
Intl. Conference on Computer Vision and Pattern Recognition. CVPR 2018. Salt Lake City, Utah. June 2018.
[arXiv][code] [bibtex]

Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, Kai-Wei Chang.
North American Chapter of the Association for Computational Linguistics. NAACL 2018. short.
New Orleans, Louisiana. June 2018.
[arXiv] [code] [bibtex]

Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, Kai-Wei Chang.
Empirical Methods in Natural Language Processing. EMNLP 2017. Copenhagen, Denmark. September 2017.
[arxiv] [code] [bibtex](Best Long Paper Award!)

Name Tagging for Low-resource Incident Languages based on Expectation-driven Learning
Boliang Zhang, Xiaoman Pan, Tianlu Wang, Ashish Vaswani, Heng Ji, Kevin Knight and Daniel Marcu
North American Chapter of the Association for Computational Linguistics. NAACL 2016
[pdf]