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2020 – today
- 2026
[i28]Chenglei Si, Zitong Yang, Yejin Choi, Emmanuel J. Candès, Diyi Yang, Tatsunori Hashimoto:
Towards Execution-Grounded Automated AI Research. CoRR abs/2601.14525 (2026)- 2025
- [c17]Dora Zhao, Qianou Ma, Xinran Zhao, Chenglei Si, Chenyang Yang, Ryan Louie, Ehud Reiter, Diyi Yang, Tongshuang Wu:
SPHERE: An Evaluation Card for Human-AI Systems. ACL (Findings) 2025: 1340-1365 - [c16]Yitao Liu, Chenglei Si, Karthik R. Narasimhan, Shunyu Yao:
Contextual Experience Replay for Self-Improvement of Language Agents. ACL (1) 2025: 14179-14198 - [c15]Chenglei Si, Diyi Yang, Tatsunori Hashimoto:
Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers. ICLR 2025 - [c14]Chenglei Si, Yanzhe Zhang, Ryan Li, Zhengyuan Yang, Ruibo Liu, Diyi Yang:
Design2Code: Benchmarking Multimodal Code Generation for Automated Front-End Engineering. NAACL (Long Papers) 2025: 3956-3974 - [i27]Qianou Ma, Dora Zhao, Xinran Zhao, Chenglei Si, Chenyang Yang, Ryan Louie, Ehud Reiter, Diyi Yang, Tongshuang Wu:
SPHERE: An Evaluation Card for Human-AI Systems. CoRR abs/2504.07971 (2025) - [i26]Jiaxin Wen, Chenglei Si, Yueh-han Chen, He He, Shi Feng:
Predicting Empirical AI Research Outcomes with Language Models. CoRR abs/2506.00794 (2025) - [i25]Yitao Liu, Chenglei Si, Karthik Narasimhan, Shunyu Yao:
Contextual Experience Replay for Self-Improvement of Language Agents. CoRR abs/2506.06698 (2025) - [i24]Chenglei Si, Tatsunori Hashimoto, Diyi Yang:
The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas. CoRR abs/2506.20803 (2025) - [i23]Xinran Zhao, Boyuan Zheng, Chenglei Si, Haofei Yu, Ken Liu, Runlong Zhou, Ruochen Li, Tong Chen, Xiang Li, Yiming Zhang, Tongshuang Wu:
The Ramon Llull's Thinking Machine for Automated Ideation. CoRR abs/2508.19200 (2025) - [i22]Shannon Zejiang Shen, Valerie Chen, Ken Gu, Alexis Ross, Zixian Ma, Jillian Ross, Alex Gu, Chenglei Si, Wayne Chi, Andi Peng, Jocelyn J. Shen, Ameet Talwalkar, Tongshuang Wu, David A. Sontag:
Completion ≠ Collaboration: Scaling Collaborative Effort with Agents. CoRR abs/2510.25744 (2025) - 2024
- [c13]Chenglei Si, Navita Goyal, Tongshuang Wu, Chen Zhao, Shi Feng, Hal Daumé III, Jordan L. Boyd-Graber:
Large Language Models Help Humans Verify Truthfulness - Except When They Are Convincingly Wrong. NAACL-HLT 2024: 1459-1474 - [i21]Chenglei Si, Yanzhe Zhang, Zhengyuan Yang, Ruibo Liu, Diyi Yang:
Design2Code: How Far Are We From Automating Front-End Engineering? CoRR abs/2403.03163 (2024) - [i20]Ruibo Liu, Jerry Wei, Fangyu Liu, Chenglei Si, Yanzhe Zhang, Jinmeng Rao, Steven Zheng, Daiyi Peng, Diyi Yang, Denny Zhou, Andrew M. Dai:
Best Practices and Lessons Learned on Synthetic Data for Language Models. CoRR abs/2404.07503 (2024) - [i19]Sander Schulhoff, Michael Ilie, Nishant Balepur, Konstantine Kahadze, Amanda Liu, Chenglei Si, Yinheng Li, Aayush Gupta, HyoJung Han, Sevien Schulhoff, Pranav Sandeep Dulepet, Saurav Vidyadhara, Dayeon Ki, Sweta Agrawal, Chau Pham, Gerson C. Kroiz, Feileen Li, Hudson Tao, Ashay Srivastava, Hevander Da Costa, Saloni Gupta, Megan L. Rogers, Inna Goncearenco, Giuseppe Sarli, Igor Galynker, Denis Peskoff, Marine Carpuat, Jules White, Shyamal Anadkat, Alexander Miserlis Hoyle
, Philip Resnik:
The Prompt Report: A Systematic Survey of Prompting Techniques. CoRR abs/2406.06608 (2024) - [i18]Hua Shen, Tiffany Knearem, Reshmi Ghosh, Kenan Alkiek, Kundan Krishna, Yachuan Liu, Ziqiao Ma, Savvas Petridis, Yi-Hao Peng, Li Qiwei, Sushrita Rakshit, Chenglei Si, Yutong Xie, Jeffrey P. Bigham, Frank Bentley, Joyce Chai, Zachary C. Lipton, Qiaozhu Mei, Rada Mihalcea, Michael Terry, Diyi Yang, Meredith Ringel Morris, Paul Resnick, David Jurgens:
Towards Bidirectional Human-AI Alignment: A Systematic Review for Clarifications, Framework, and Future Directions. CoRR abs/2406.09264 (2024) - [i17]Chaojun Xiao, Zhengyan Zhang, Chenyang Song, Dazhi Jiang, Feng Yao, Xu Han, Xiaozhi Wang, Shuo Wang, Yufei Huang, Guanyu Lin, Yingfa Chen, Weilin Zhao, Yuge Tu, Zexuan Zhong, Ao Zhang, Chenglei Si, Moo Khai Hao, Chenyang Zhao, Huimin Chen, Yankai Lin, Zhiyuan Liu, Jingbo Shang, Maosong Sun:
Configurable Foundation Models: Building LLMs from a Modular Perspective. CoRR abs/2409.02877 (2024) - [i16]Chenglei Si, Diyi Yang, Tatsunori Hashimoto:
Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers. CoRR abs/2409.04109 (2024) - 2023
- [j1]Chenglei Si, Zhengyan Zhang, Yingfa Chen, Fanchao Qi, Xiaozhi Wang, Zhiyuan Liu, Yasheng Wang, Qun Liu, Maosong Sun:
Sub-Character Tokenization for Chinese Pretrained Language Models. Trans. Assoc. Comput. Linguistics 11: 469-487 (2023) - [c12]Chenglei Si, Zhengyan Zhang, Yingfa Chen, Xiaozhi Wang, Zhiyuan Liu, Maosong Sun:
READIN: A Chinese Multi-Task Benchmark with Realistic and Diverse Input Noises. ACL (1) 2023: 8272-8285 - [c11]Chenglei Si, Dan Friedman, Nitish Joshi, Shi Feng, Danqi Chen, He He:
Measuring Inductive Biases of In-Context Learning with Underspecified Demonstrations. ACL (1) 2023: 11289-11310 - [c10]Sander Schulhoff, Jeremy Pinto, Anaum Khan, Louis-François Bouchard, Chenglei Si, Svetlina Anati, Valen Tagliabue, Anson Liu Kost, Christopher Carnahan, Jordan L. Boyd-Graber:
Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs Through a Global Prompt Hacking Competition. EMNLP 2023: 4945-4977 - [c9]Chenglei Si, Weijia Shi, Chen Zhao, Luke Zettlemoyer, Jordan L. Boyd-Graber:
Getting MoRE out of Mixture of Language Model Reasoning Experts. EMNLP (Findings) 2023: 8234-8249 - [c8]Chenglei Si, Zhe Gan, Zhengyuan Yang, Shuohang Wang, Jianfeng Wang, Jordan L. Boyd-Graber, Lijuan Wang:
Prompting GPT-3 To Be Reliable. ICLR 2023 - [i15]Chenglei Si, Zhengyan Zhang, Yingfa Chen, Xiaozhi Wang, Zhiyuan Liu, Maosong Sun:
READIN: A Chinese Multi-Task Benchmark with Realistic and Diverse Input Noises. CoRR abs/2302.07324 (2023) - [i14]Chenglei Si, Dan Friedman, Nitish Joshi, Shi Feng, Danqi Chen, He He:
Measuring Inductive Biases of In-Context Learning with Underspecified Demonstrations. CoRR abs/2305.13299 (2023) - [i13]Chenglei Si, Weijia Shi, Chen Zhao, Luke Zettlemoyer, Jordan L. Boyd-Graber:
Mixture of Prompt Experts for Generalizable and Interpretable Question Answering. CoRR abs/2305.14628 (2023) - [i12]Chenglei Si, Navita Goyal, Sherry Tongshuang Wu, Chen Zhao, Shi Feng, Hal Daumé III, Jordan L. Boyd-Graber:
Large Language Models Help Humans Verify Truthfulness - Except When They Are Convincingly Wrong. CoRR abs/2310.12558 (2023) - [i11]Sander Schulhoff, Jeremy Pinto, Anaum Khan, Louis-François Bouchard, Chenglei Si, Svetlina Anati, Valen Tagliabue, Anson Liu Kost, Christopher Carnahan, Jordan L. Boyd-Graber:
Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs through a Global Scale Prompt Hacking Competition. CoRR abs/2311.16119 (2023) - 2022
- [c7]Chenglei Si, Chen Zhao, Sewon Min, Jordan L. Boyd-Graber:
Re-Examining Calibration: The Case of Question Answering. EMNLP (Findings) 2022: 2814-2829 - [i10]Chenglei Si, Chen Zhao, Sewon Min, Jordan L. Boyd-Graber:
Revisiting Calibration for Question Answering. CoRR abs/2205.12507 (2022) - [i9]Chenglei Si, Zhe Gan, Zhengyuan Yang, Shuohang Wang, Jianfeng Wang, Jordan L. Boyd-Graber, Lijuan Wang:
Prompting GPT-3 To Be Reliable. CoRR abs/2210.09150 (2022) - 2021
- [c6]Chenglei Si, Ziqing Yang, Yiming Cui, Wentao Ma, Ting Liu, Shijin Wang:
Benchmarking Robustness of Machine Reading Comprehension Models. ACL/IJCNLP (Findings) 2021: 634-644 - [c5]Chenglei Si, Zhengyan Zhang, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Qun Liu, Maosong Sun:
Better Robustness by More Coverage: Adversarial and Mixup Data Augmentation for Robust Finetuning. ACL/IJCNLP (Findings) 2021: 1569-1576 - [c4]Chenglei Si, Chen Zhao, Jordan L. Boyd-Graber:
What's in a Name? Answer Equivalence For Open-Domain Question Answering. EMNLP (1) 2021: 9623-9629 - [c3]Ziqing Yang, Yiming Cui, Chenglei Si, Wanxiang Che, Ting Liu, Shijin Wang, Guoping Hu:
Adversarial Training for Machine Reading Comprehension with Virtual Embeddings. *SEM 2021: 308-313 - [i8]Chenglei Si, Zhengyan Zhang, Yingfa Chen, Fanchao Qi, Xiaozhi Wang, Zhiyuan Liu, Maosong Sun:
SHUOWEN-JIEZI: Linguistically Informed Tokenizers For Chinese Language Model Pretraining. CoRR abs/2106.00400 (2021) - [i7]Ziqing Yang, Yiming Cui, Chenglei Si, Wanxiang Che, Ting Liu, Shijin Wang, Guoping Hu:
Adversarial Training for Machine Reading Comprehension with Virtual Embeddings. CoRR abs/2106.04437 (2021) - [i6]Chenglei Si, Chen Zhao, Jordan L. Boyd-Graber:
What's in a Name? Answer Equivalence For Open-Domain Question Answering. CoRR abs/2109.05289 (2021) - [i5]Sabrina J. Mielke, Zaid Alyafeai, Elizabeth Salesky, Colin Raffel, Manan Dey, Matthias Gallé, Arun Raja, Chenglei Si, Wilson Y. Lee, Benoît Sagot, Samson Tan:
Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP. CoRR abs/2112.10508 (2021) - 2020
- [c2]Wentao Ma, Yiming Cui, Chenglei Si, Ting Liu, Shijin Wang, Guoping Hu:
CharBERT: Character-aware Pre-trained Language Model. COLING 2020: 39-50 - [i4]Chenglei Si, Ziqing Yang, Yiming Cui, Wentao Ma, Ting Liu, Shijin Wang:
Benchmarking Robustness of Machine Reading Comprehension Models. CoRR abs/2004.14004 (2020) - [i3]Wentao Ma, Yiming Cui, Chenglei Si, Ting Liu, Shijin Wang, Guoping Hu:
CharBERT: Character-aware Pre-trained Language Model. CoRR abs/2011.01513 (2020) - [i2]Chenglei Si, Zhengyan Zhang, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Qun Liu, Maosong Sun:
Better Robustness by More Coverage: Adversarial Training with Mixup Augmentation for Robust Fine-tuning. CoRR abs/2012.15699 (2020)
2010 – 2019
- 2019
- [c1]Chenglei Si, Kui Wu, Ai Ti Aw, Min-Yen Kan:
Sentiment Aware Neural Machine Translation. WAT@EMNLP-IJCNLP 2019: 200-206 - [i1]Chenglei Si, Shuohang Wang, Min-Yen Kan, Jing Jiang:
What does BERT Learn from Multiple-Choice Reading Comprehension Datasets? CoRR abs/1910.12391 (2019)
Coauthor Index
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last updated on 2026-02-27 00:16 CET by the dblp team
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