Probabilistic Graph-based Dependency Parsing with Convolutional Neural Network. - Zhisong Zhang; Hai Zhao; Lianhui Qin (ACL (1), 2016)

Implicit Discourse Relation Recognition with Context-aware Character-enhanced Embeddings. - Lianhui Qin; Zhisong Zhang; Hai Zhao (COLING, 2016)

Shallow Discourse Parsing Using Convolutional Neural Network. - Lianhui Qin; Zhisong Zhang; Hai Zhao (CoNLL Shared Task, 2016)

A Stacking Gated Neural Architecture for Implicit Discourse Relation Classification. - Lianhui Qin; Zhisong Zhang; Hai Zhao (EMNLP, 2016)

Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification. - Lianhui Qin; Zhisong Zhang; Hai Zhao; Zhiting Hu; Eric P. Xing (ACL (1), 2017)

Automatic Article Commenting: the Task and Dataset. - Lianhui Qin; Lemao Liu; Victoria Bi; Yan Wang 060; Xiaojiang Liu; Zhiting Hu; Hai Zhao; Shuming Shi 001 (ACL (2), 2018)

Deep Generative Models with Learnable Knowledge Constraints. - Zhiting Hu; Zichao Yang; Ruslan Salakhutdinov; Lianhui Qin; Xiaodan Liang; Haoye Dong; Eric P. Xing (NeurIPS, 2018)

Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation. - Zhiting Hu; Haoran Shi 001; Zichao Yang; Bowen Tan; Tiancheng Zhao; Junxian He; Wentao Wang; Xingjiang Yu; Lianhui Qin; Di Wang 030; Xuezhe Ma; Zhengzhong Liu 001; et al. (CoRR, 2018)

Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation. - Zhiting Hu; Haoran Shi 001; Bowen Tan; Wentao Wang; Zichao Yang; Tiancheng Zhao; Junxian He; Lianhui Qin; Di Wang 030; Xuezhe Ma; Zhengzhong Liu 001; Xiaodan Liang; et al. (ACL (3), 2019)

Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading. - Lianhui Qin; Michel Galley; Chris Brockett; Xiaodong Liu 003; Xiang Gao 011; Bill Dolan; Yejin Choi 001; Jianfeng Gao 001 (ACL (1), 2019)

Counterfactual Story Reasoning and Generation. - Lianhui Qin; Antoine Bosselut; Ari Holtzman; Chandra Bhagavatula; Elizabeth Clark; Yejin Choi 001 (EMNLP/IJCNLP (1), 2019)

Social Bias Frames: Reasoning about Social and Power Implications of Language. - Maarten Sap; Saadia Gabriel; Lianhui Qin; Dan Jurafsky; Noah A. Smith; Yejin Choi 001 (ACL, 2020)

Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning. - Lianhui Qin; Vered Shwartz; Peter West; Chandra Bhagavatula; Jena D. Hwang; Ronan Le Bras 001; Antoine Bosselut; Yejin Choi 001 (EMNLP (1), 2020)

Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach. - Bowen Tan; Lianhui Qin; Eric P. Xing; Zhiting Hu (EMNLP (1), 2020)

Evaluating Machines by their Real-World Language Use. - Rowan Zellers; Ari Holtzman; Elizabeth Clark; Lianhui Qin; Ali Farhadi; Yejin Choi 001 (CoRR, 2020)

TIMEDIAL: Temporal Commonsense Reasoning in Dialog. - Lianhui Qin; Aditya Gupta; Shyam Upadhyay; Luheng He; Yejin Choi 001; Manaal Faruqui (ACL/IJCNLP (1), 2021)

TuringAdvice: A Generative and Dynamic Evaluation of Language Use. - Rowan Zellers; Ari Holtzman; Elizabeth Clark; Lianhui Qin; Ali Farhadi; Yejin Choi 001 (NAACL-HLT, 2021)

PROMPT WAYWARDNESS: The Curious Case of Discretized Interpretation of Continuous Prompts. - Daniel Khashabi; Shane Lyu; Sewon Min; Lianhui Qin; Kyle Richardson 001; Sameer Singh 001; Sean Welleck; Hannaneh Hajishirzi; Tushar Khot; Ashish Sabharwal; Yejin Choi 001 (CoRR, 2021)

Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts. - Wenhao Yu 002; Chenguang Zhu 001; Lianhui Qin; Zhihan Zhang 001; Tong Zhao 003; Meng Jiang 001 (ACL (Findings), 2022)

Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations. - Jaehun Jung; Lianhui Qin; Sean Welleck; Faeze Brahman; Chandra Bhagavatula; Ronan Le Bras 001; Yejin Choi 001 (EMNLP, 2022)

Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts. - Daniel Khashabi; Xinxi Lyu; Sewon Min; Lianhui Qin; Kyle Richardson 001; Sean Welleck; Hannaneh Hajishirzi; Tushar Khot; Ashish Sabharwal; Sameer Singh 001; Yejin Choi 001 (NAACL-HLT, 2022)

NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics. - Ximing Lu; Sean Welleck; Peter West; Liwei Jiang; Jungo Kasai; Daniel Khashabi; Ronan Le Bras 001; Lianhui Qin; Youngjae Yu; Rowan Zellers; Noah A. Smith; Yejin Choi 001 (NAACL-HLT, 2022)

QUARK: Controllable Text Generation with Reinforced Unlearning. - Ximing Lu; Sean Welleck; Jack Hessel; Liwei Jiang; Lianhui Qin; Peter West; Prithviraj Ammanabrolu; Yejin Choi 001 (NeurIPS, 2022)

COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics. - Lianhui Qin; Sean Welleck; Daniel Khashabi; Yejin Choi 001 (NeurIPS, 2022)

I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation. - Chandra Bhagavatula; Jena D. Hwang; Doug Downey; Ronan Le Bras 001; Ximing Lu; Lianhui Qin; Keisuke Sakaguchi; Swabha Swayamdipta; Peter West; Yejin Choi 001 (ACL (1), 2023)

Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. - Ximing Lu; Faeze Brahman; Peter West; Jaehun Jung; Khyathi Raghavi Chandu; Abhilasha Ravichander; Prithviraj Ammanabrolu; Liwei Jiang; Sahana Ramnath; Nouha Dziri; Jillian Fisher; Bill Y. Lin; et al. (EMNLP, 2023)

Structured Chemistry Reasoning with Large Language Models. - Siru Ouyang; Zhuosheng Zhang 001; Bing Yan; Xuan Liu 009; Jiawei Han 001; Lianhui Qin (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Constrained, Causal, and Knowledge-Grounded Reasoning for Neural Language Generation - Lianhui Qin (2023)

COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability. - Xingang Guo; Fangxu Yu; Huan Zhang; Lianhui Qin; Bin Hu 002 (ICML, 2024)

Structured Chemistry Reasoning with Large Language Models. - Siru Ouyang; Zhuosheng Zhang 001; Bing Yan; Xuan Liu 009; Yejin Choi 001; Jiawei Han 001; Lianhui Qin (ICML, 2024)

MacGyver: Are Large Language Models Creative Problem Solvers? - Yufei Tian; Abhilasha Ravichander; Lianhui Qin; Ronan Le Bras 001; Raja Marjieh; Nanyun Peng 001; Yejin Choi 001; Thomas L. Griffiths 001; Faeze Brahman (NAACL-HLT, 2024)

LLMs-based Few-Shot Disease Predictions using EHR: A Novel Approach Combining Predictive Agent Reasoning and Critical Agent Instruction. - Hejie Cui; Zhuocheng Shen; Jieyu Zhang 001; Hui Shao; Lianhui Qin; Joyce C. Ho; Carl Yang 001 (CoRR, 2024)

Capabilities of Large Language Models in Control Engineering: A Benchmark Study on GPT-4, Claude 3 Opus, and Gemini 1.0 Ultra. - Darioush Kevian; Usman Syed; Xingang Guo; Aaron J. Havens; Geir E. Dullerud; Peter J. Seiler; Lianhui Qin; Bin Hu 002 (CoRR, 2024)

EduAgent: Generative Student Agents in Learning. - Songlin Xu; Xinyu Zhang; Lianhui Qin (CoRR, 2024)

Flow of Reasoning: Efficient Training of LLM Policy with Divergent Thinking. - Fangxu Yu; Lai Jiang; Haoqiang Kang; Shibo Hao; Lianhui Qin (CoRR, 2024)

WeatherQA: Can Multimodal Language Models Reason about Severe Weather? - Chengqian Ma; Zhanxiang Hua; Alexandra Anderson-Frey; Vikram Iyer; Xin Liu 034; Lianhui Qin (CoRR, 2024)

Benchmarking the Capabilities of Large Language Models in Transportation System Engineering: Accuracy, Consistency, and Reasoning Behaviors. - Usman Syed; Ethan Light; Xingang Guo; Huan Zhang; Lianhui Qin; Yanfeng Ouyang; Bin Hu 002 (CoRR, 2024)

ControlAgent: Automating Control System Design via Novel Integration of LLM Agents and Domain Expertise. - Xingang Guo; Darioush Keivan; Usman Syed; Lianhui Qin; Huan Zhang; Geir E. Dullerud; Peter J. Seiler; Bin Hu 002 (CoRR, 2024)

Political-LLM: Large Language Models in Political Science. - Lincan Li; Jiaqi Li; Catherine Chen 003; Fred Gui; Hongjia Yang; Chenxiao Yu; Zhengguang Wang; Jianing Cai; Junlong Aaron Zhou; Bolin Shen; Alex Qian; Weixin Chen; et al. (CoRR, 2024)

From Classification to Clinical Insights: Towards Analyzing and Reasoning About Mobile and Behavioral Health Data With Large Language Models. - Zachary Englhardt; Chengqian Ma; Margaret E. Morris; Chun-Cheng Chang; Xuhai Xu; Lianhui Qin; Daniel McDuff; Xin Liu 034; Shwetak N. Patel; Vikram Iyer (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2024)

Do Vision-Language Models Have Internal World Models? Towards an Atomic Evaluation. - Qiyue Gao; Xinyu Pi; Kevin Liu; Junrong Chen; Ruolan Yang; Xinqi Huang; Xinyu Fang; Lu Sun; Gautham Kishore; Bo Ai 008; Stone Tao; Mengyang Liu; et al. (ACL (Findings), 2025)

Collaborating Action by Action: A Multi-agent LLM Framework for Embodied Reasoning. - Isadora White; Kolby Nottingham; Ayush Maniar; Max Robinson; Hansen Lillemark; Mehul Maheshwari; Lianhui Qin; Prithviraj Ammanabrolu (CoRR, 2025)

Compiler Optimization via LLM Reasoning for Efficient Model Serving. - Sujun Tang; Christopher Priebe; Rohan Mahapatra; Lianhui Qin; Hadi Esmaeilzadeh (CoRR, 2025)

KVFlow: Efficient Prefix Caching for Accelerating LLM-Based Multi-Agent Workflows. - Zaifeng Pan; Ajjkumar Patel; Zhengding Hu; Yipeng Shen; Yue Guan; Wan-Lu Li; Lianhui Qin; Yida Wang; Yufei Ding 001 (CoRR, 2025)